Review of recent advances in petroleum fluid properties and their representation
It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more im...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Dindoruk, Birol [verfasserIn] Ratnakar, Ram R. [verfasserIn] He, Jiajun [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Journal of natural gas science and engineering - Amsterdam [u.a.] : Elsevier, 2009, 83 |
|---|---|
| Übergeordnetes Werk: |
volume:83 |
| DOI / URN: |
10.1016/j.jngse.2020.103541 |
|---|
| Katalog-ID: |
ELV004850319 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV004850319 | ||
| 003 | DE-627 | ||
| 005 | 20230524131249.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230503s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.jngse.2020.103541 |2 doi | |
| 035 | |a (DE-627)ELV004850319 | ||
| 035 | |a (ELSEVIER)S1875-5100(20)30395-4 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 660 |q DE-600 |
| 100 | 1 | |a Dindoruk, Birol |e verfasserin |0 (orcid)0000-0002-9759-8007 |4 aut | |
| 245 | 1 | 0 | |a Review of recent advances in petroleum fluid properties and their representation |
| 264 | 1 | |c 2020 | |
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. | ||
| 650 | 4 | |a PVT - pressure volume and temperature | |
| 650 | 4 | |a PVT State of the art | |
| 650 | 4 | |a Equation of State (EOS) | |
| 650 | 4 | |a PVT New Developments | |
| 650 | 4 | |a Microfluidics | |
| 650 | 4 | |a Machine Learning - PVT | |
| 700 | 1 | |a Ratnakar, Ram R. |e verfasserin |0 (orcid)0000-0002-1869-7673 |4 aut | |
| 700 | 1 | |a He, Jiajun |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of natural gas science and engineering |d Amsterdam [u.a.] : Elsevier, 2009 |g 83 |h Online-Ressource |w (DE-627)608943231 |w (DE-600)2514802-3 |w (DE-576)311098436 |x 1875-5100 |7 nnns |
| 773 | 1 | 8 | |g volume:83 |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_32 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_60 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_63 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_74 | ||
| 912 | |a GBV_ILN_90 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_100 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_150 | ||
| 912 | |a GBV_ILN_151 | ||
| 912 | |a GBV_ILN_165 | ||
| 912 | |a GBV_ILN_224 | ||
| 912 | |a GBV_ILN_370 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_702 | ||
| 912 | |a GBV_ILN_2003 | ||
| 912 | |a GBV_ILN_2004 | ||
| 912 | |a GBV_ILN_2005 | ||
| 912 | |a GBV_ILN_2006 | ||
| 912 | |a GBV_ILN_2008 | ||
| 912 | |a GBV_ILN_2011 | ||
| 912 | |a GBV_ILN_2014 | ||
| 912 | |a GBV_ILN_2015 | ||
| 912 | |a GBV_ILN_2020 | ||
| 912 | |a GBV_ILN_2021 | ||
| 912 | |a GBV_ILN_2025 | ||
| 912 | |a GBV_ILN_2027 | ||
| 912 | |a GBV_ILN_2034 | ||
| 912 | |a GBV_ILN_2038 | ||
| 912 | |a GBV_ILN_2044 | ||
| 912 | |a GBV_ILN_2048 | ||
| 912 | |a GBV_ILN_2049 | ||
| 912 | |a GBV_ILN_2050 | ||
| 912 | |a GBV_ILN_2056 | ||
| 912 | |a GBV_ILN_2059 | ||
| 912 | |a GBV_ILN_2061 | ||
| 912 | |a GBV_ILN_2064 | ||
| 912 | |a GBV_ILN_2065 | ||
| 912 | |a GBV_ILN_2068 | ||
| 912 | |a GBV_ILN_2088 | ||
| 912 | |a GBV_ILN_2111 | ||
| 912 | |a GBV_ILN_2112 | ||
| 912 | |a GBV_ILN_2113 | ||
| 912 | |a GBV_ILN_2118 | ||
| 912 | |a GBV_ILN_2122 | ||
| 912 | |a GBV_ILN_2129 | ||
| 912 | |a GBV_ILN_2143 | ||
| 912 | |a GBV_ILN_2147 | ||
| 912 | |a GBV_ILN_2148 | ||
| 912 | |a GBV_ILN_2152 | ||
| 912 | |a GBV_ILN_2153 | ||
| 912 | |a GBV_ILN_2190 | ||
| 912 | |a GBV_ILN_2470 | ||
| 912 | |a GBV_ILN_2507 | ||
| 912 | |a GBV_ILN_2522 | ||
| 912 | |a GBV_ILN_4035 | ||
| 912 | |a GBV_ILN_4037 | ||
| 912 | |a GBV_ILN_4046 | ||
| 912 | |a GBV_ILN_4112 | ||
| 912 | |a GBV_ILN_4125 | ||
| 912 | |a GBV_ILN_4126 | ||
| 912 | |a GBV_ILN_4242 | ||
| 912 | |a GBV_ILN_4251 | ||
| 912 | |a GBV_ILN_4305 | ||
| 912 | |a GBV_ILN_4313 | ||
| 912 | |a GBV_ILN_4322 | ||
| 912 | |a GBV_ILN_4323 | ||
| 912 | |a GBV_ILN_4324 | ||
| 912 | |a GBV_ILN_4325 | ||
| 912 | |a GBV_ILN_4326 | ||
| 912 | |a GBV_ILN_4333 | ||
| 912 | |a GBV_ILN_4334 | ||
| 912 | |a GBV_ILN_4335 | ||
| 912 | |a GBV_ILN_4338 | ||
| 912 | |a GBV_ILN_4393 | ||
| 951 | |a AR | ||
| 952 | |d 83 | ||
| author_variant |
b d bd r r r rr rrr j h jh |
|---|---|
| matchkey_str |
article:18755100:2020----::eiwfeetdacsnerlufudrprisn |
| hierarchy_sort_str |
2020 |
| publishDate |
2020 |
| allfields |
10.1016/j.jngse.2020.103541 doi (DE-627)ELV004850319 (ELSEVIER)S1875-5100(20)30395-4 DE-627 ger DE-627 rda eng 660 DE-600 Dindoruk, Birol verfasserin (orcid)0000-0002-9759-8007 aut Review of recent advances in petroleum fluid properties and their representation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. PVT - pressure volume and temperature PVT State of the art Equation of State (EOS) PVT New Developments Microfluidics Machine Learning - PVT Ratnakar, Ram R. verfasserin (orcid)0000-0002-1869-7673 aut He, Jiajun verfasserin aut Enthalten in Journal of natural gas science and engineering Amsterdam [u.a.] : Elsevier, 2009 83 Online-Ressource (DE-627)608943231 (DE-600)2514802-3 (DE-576)311098436 1875-5100 nnns volume:83 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_165 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 83 |
| spelling |
10.1016/j.jngse.2020.103541 doi (DE-627)ELV004850319 (ELSEVIER)S1875-5100(20)30395-4 DE-627 ger DE-627 rda eng 660 DE-600 Dindoruk, Birol verfasserin (orcid)0000-0002-9759-8007 aut Review of recent advances in petroleum fluid properties and their representation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. PVT - pressure volume and temperature PVT State of the art Equation of State (EOS) PVT New Developments Microfluidics Machine Learning - PVT Ratnakar, Ram R. verfasserin (orcid)0000-0002-1869-7673 aut He, Jiajun verfasserin aut Enthalten in Journal of natural gas science and engineering Amsterdam [u.a.] : Elsevier, 2009 83 Online-Ressource (DE-627)608943231 (DE-600)2514802-3 (DE-576)311098436 1875-5100 nnns volume:83 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_165 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 83 |
| allfields_unstemmed |
10.1016/j.jngse.2020.103541 doi (DE-627)ELV004850319 (ELSEVIER)S1875-5100(20)30395-4 DE-627 ger DE-627 rda eng 660 DE-600 Dindoruk, Birol verfasserin (orcid)0000-0002-9759-8007 aut Review of recent advances in petroleum fluid properties and their representation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. PVT - pressure volume and temperature PVT State of the art Equation of State (EOS) PVT New Developments Microfluidics Machine Learning - PVT Ratnakar, Ram R. verfasserin (orcid)0000-0002-1869-7673 aut He, Jiajun verfasserin aut Enthalten in Journal of natural gas science and engineering Amsterdam [u.a.] : Elsevier, 2009 83 Online-Ressource (DE-627)608943231 (DE-600)2514802-3 (DE-576)311098436 1875-5100 nnns volume:83 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_165 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 83 |
| allfieldsGer |
10.1016/j.jngse.2020.103541 doi (DE-627)ELV004850319 (ELSEVIER)S1875-5100(20)30395-4 DE-627 ger DE-627 rda eng 660 DE-600 Dindoruk, Birol verfasserin (orcid)0000-0002-9759-8007 aut Review of recent advances in petroleum fluid properties and their representation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. PVT - pressure volume and temperature PVT State of the art Equation of State (EOS) PVT New Developments Microfluidics Machine Learning - PVT Ratnakar, Ram R. verfasserin (orcid)0000-0002-1869-7673 aut He, Jiajun verfasserin aut Enthalten in Journal of natural gas science and engineering Amsterdam [u.a.] : Elsevier, 2009 83 Online-Ressource (DE-627)608943231 (DE-600)2514802-3 (DE-576)311098436 1875-5100 nnns volume:83 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_165 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 83 |
| allfieldsSound |
10.1016/j.jngse.2020.103541 doi (DE-627)ELV004850319 (ELSEVIER)S1875-5100(20)30395-4 DE-627 ger DE-627 rda eng 660 DE-600 Dindoruk, Birol verfasserin (orcid)0000-0002-9759-8007 aut Review of recent advances in petroleum fluid properties and their representation 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. PVT - pressure volume and temperature PVT State of the art Equation of State (EOS) PVT New Developments Microfluidics Machine Learning - PVT Ratnakar, Ram R. verfasserin (orcid)0000-0002-1869-7673 aut He, Jiajun verfasserin aut Enthalten in Journal of natural gas science and engineering Amsterdam [u.a.] : Elsevier, 2009 83 Online-Ressource (DE-627)608943231 (DE-600)2514802-3 (DE-576)311098436 1875-5100 nnns volume:83 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_165 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 83 |
| language |
English |
| source |
Enthalten in Journal of natural gas science and engineering 83 volume:83 |
| sourceStr |
Enthalten in Journal of natural gas science and engineering 83 volume:83 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
PVT - pressure volume and temperature PVT State of the art Equation of State (EOS) PVT New Developments Microfluidics Machine Learning - PVT |
| dewey-raw |
660 |
| isfreeaccess_bool |
false |
| container_title |
Journal of natural gas science and engineering |
| authorswithroles_txt_mv |
Dindoruk, Birol @@aut@@ Ratnakar, Ram R. @@aut@@ He, Jiajun @@aut@@ |
| publishDateDaySort_date |
2020-01-01T00:00:00Z |
| hierarchy_top_id |
608943231 |
| dewey-sort |
3660 |
| id |
ELV004850319 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV004850319</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524131249.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230503s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.jngse.2020.103541</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV004850319</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1875-5100(20)30395-4</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">660</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Dindoruk, Birol</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-9759-8007</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Review of recent advances in petroleum fluid properties and their representation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PVT - pressure volume and temperature</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PVT State of the art</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Equation of State (EOS)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PVT New Developments</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Microfluidics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine Learning - PVT</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ratnakar, Ram R.</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-1869-7673</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Jiajun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of natural gas science and engineering</subfield><subfield code="d">Amsterdam [u.a.] : Elsevier, 2009</subfield><subfield code="g">83</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)608943231</subfield><subfield code="w">(DE-600)2514802-3</subfield><subfield code="w">(DE-576)311098436</subfield><subfield code="x">1875-5100</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:83</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">83</subfield></datafield></record></collection>
|
| author |
Dindoruk, Birol |
| spellingShingle |
Dindoruk, Birol ddc 660 misc PVT - pressure volume and temperature misc PVT State of the art misc Equation of State (EOS) misc PVT New Developments misc Microfluidics misc Machine Learning - PVT Review of recent advances in petroleum fluid properties and their representation |
| authorStr |
Dindoruk, Birol |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)608943231 |
| format |
electronic Article |
| dewey-ones |
660 - Chemical engineering |
| delete_txt_mv |
keep |
| author_role |
aut aut aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| issn |
1875-5100 |
| topic_title |
660 DE-600 Review of recent advances in petroleum fluid properties and their representation PVT - pressure volume and temperature PVT State of the art Equation of State (EOS) PVT New Developments Microfluidics Machine Learning - PVT |
| topic |
ddc 660 misc PVT - pressure volume and temperature misc PVT State of the art misc Equation of State (EOS) misc PVT New Developments misc Microfluidics misc Machine Learning - PVT |
| topic_unstemmed |
ddc 660 misc PVT - pressure volume and temperature misc PVT State of the art misc Equation of State (EOS) misc PVT New Developments misc Microfluidics misc Machine Learning - PVT |
| topic_browse |
ddc 660 misc PVT - pressure volume and temperature misc PVT State of the art misc Equation of State (EOS) misc PVT New Developments misc Microfluidics misc Machine Learning - PVT |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Journal of natural gas science and engineering |
| hierarchy_parent_id |
608943231 |
| dewey-tens |
660 - Chemical engineering |
| hierarchy_top_title |
Journal of natural gas science and engineering |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)608943231 (DE-600)2514802-3 (DE-576)311098436 |
| title |
Review of recent advances in petroleum fluid properties and their representation |
| ctrlnum |
(DE-627)ELV004850319 (ELSEVIER)S1875-5100(20)30395-4 |
| title_full |
Review of recent advances in petroleum fluid properties and their representation |
| author_sort |
Dindoruk, Birol |
| journal |
Journal of natural gas science and engineering |
| journalStr |
Journal of natural gas science and engineering |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
zzz |
| author_browse |
Dindoruk, Birol Ratnakar, Ram R. He, Jiajun |
| container_volume |
83 |
| class |
660 DE-600 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Dindoruk, Birol |
| doi_str_mv |
10.1016/j.jngse.2020.103541 |
| normlink |
(ORCID)0000-0002-9759-8007 (ORCID)0000-0002-1869-7673 |
| normlink_prefix_str_mv |
(orcid)0000-0002-9759-8007 (orcid)0000-0002-1869-7673 |
| dewey-full |
660 |
| author2-role |
verfasserin |
| title_sort |
review of recent advances in petroleum fluid properties and their representation |
| title_auth |
Review of recent advances in petroleum fluid properties and their representation |
| abstract |
It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. |
| abstractGer |
It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. |
| abstract_unstemmed |
It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods. |
| collection_details |
GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_165 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 |
| title_short |
Review of recent advances in petroleum fluid properties and their representation |
| remote_bool |
true |
| author2 |
Ratnakar, Ram R. He, Jiajun |
| author2Str |
Ratnakar, Ram R. He, Jiajun |
| ppnlink |
608943231 |
| mediatype_str_mv |
c |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1016/j.jngse.2020.103541 |
| up_date |
2024-07-07T00:21:23.236Z |
| _version_ |
1803877543562969088 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV004850319</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524131249.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230503s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.jngse.2020.103541</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV004850319</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1875-5100(20)30395-4</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">660</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Dindoruk, Birol</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-9759-8007</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Review of recent advances in petroleum fluid properties and their representation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">It is well-known that petroleum fluid properties (also known as Pressure-Temperature-Volume -PVT) is needed for many petroleum engineering and other interdisciplinary engineering applications. Especially in recent years, multi-disciplinary acquisition of such data and its use became more and more important as seamless and efficient integration became a necessity. Fluid properties for every step of the value chain are extremely important for project evaluation, safety and decision making along with geological and geophysical information. One of the key points about the reservoir fluids is that once the fluids enter the wellbore, all the geologic complexities and rocks will be left behind. Therefore, the focus will be more on fluid compositions and properties and how they are linked and behave within the source (reservoir) to create the maximum value. During this process, fluids are the only desired subsurface elements (with an attached commercial unit pricing) that change hands from one discipline to another discipline. Parallel to this fluids/fluid properties are evaluated for relevant applications and also used in different software applications while they move from reservoir to the wellbore and facilities and all the way to the refineries then to the sales. Therefore, there is always special focus in terms of capturing their needed properties for various applications. Along the way, we face various needs and challenges. Such needs span a wide spectrum of applications, from property valuations, health safety and environment, and all the way from reservoir to well and facilities performance de-risking and management. In this study, we focus on current state-of-the-art in this area and what the current and forward-looking advancements are while highlighting various elements of the progress. In addition, lifecycle management of the fluids and the associated information extracted with modern techniques will be included in this study. Particular attention was given to new developments in terms of hardware, sensors and miniaturization, along with numerical techniques in terms of new/coupled physics and as well as data analytics, molecular simulation, and advanced computational methods.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PVT - pressure volume and temperature</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PVT State of the art</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Equation of State (EOS)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">PVT New Developments</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Microfluidics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine Learning - PVT</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ratnakar, Ram R.</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-1869-7673</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Jiajun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of natural gas science and engineering</subfield><subfield code="d">Amsterdam [u.a.] : Elsevier, 2009</subfield><subfield code="g">83</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)608943231</subfield><subfield code="w">(DE-600)2514802-3</subfield><subfield code="w">(DE-576)311098436</subfield><subfield code="x">1875-5100</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:83</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_150</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2065</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2113</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">83</subfield></datafield></record></collection>
|
| score |
7.4010057 |