Xu Zeng, Jinying Dong, P. Zhao, Wei Liu, C. Bian, Chunlin Zhang
The division and identification of lithology and lithofacies are very important in exploration and development of oil and gas reservoirs. Information on lithofacies determines the development modes and provides the favorable "sweet spot" intervals of shales. The Chang 7-3 sub-member of the Triassic Yanchang Formation in the Longdong area of the Ordos Basin is an important shale formation in China. Core photos, cast thin sections, and log response characteristics were used to clarify the development and distribution characteristics of the various lithofacies in this formation. The lithofacies of target intervals are classified into fine grained sandy debrite, silty to fine grained sandy turbidite, fine grained sandy slump, semi-deep to deep lacustrine mudstone, and deep lacustrine shale. Further, the conventional and micro-resistivity imaging log response characteristics of different lithofacies are analyzed. Compared with other lithofacies, deep lacustrine shale facies are characterized by high gamma ray (GR), high compensated neutron log (CNL), high acoustic log (AC), and low density (DEN) log values. Crossplots of GR-AC, DEN-CNL, and DEN-AC are proposed to identify most of the lithofacies, and a criterion was established for use of well logs to characterize the lithofacies. Finally, a method joining conventional logs and micro-resistivity imaging log data was applied to field wells, achieving the very high accuracy rate of 88%. The distribution maps of different lithofacies thickness in the study area are obtained. Deep lacustrine shale faces have the widest development area and many thickness centers. Accurate and effective identification of lithofacies shows that within Ordos Basin, there is an area of about 20,000 km2 with shale thickness greater than 6 m, providing an important basis for shale oil exploration in the study area.Keywords: Continental shale oil; Lithofacies; Lacustrine shale; Micro-resistivity imaging
{"title":"Classification and well log identification of lithofacies of continental shale oil reservoirs in Chang 7-3 sub-member of Triassic Yanchang Formation in Longdong area of Ordos Basin, China","authors":"Xu Zeng, Jinying Dong, P. Zhao, Wei Liu, C. Bian, Chunlin Zhang","doi":"10.1190/int-2022-0070.1","DOIUrl":"https://doi.org/10.1190/int-2022-0070.1","url":null,"abstract":"The division and identification of lithology and lithofacies are very important in exploration and development of oil and gas reservoirs. Information on lithofacies determines the development modes and provides the favorable \"sweet spot\" intervals of shales. The Chang 7-3 sub-member of the Triassic Yanchang Formation in the Longdong area of the Ordos Basin is an important shale formation in China. Core photos, cast thin sections, and log response characteristics were used to clarify the development and distribution characteristics of the various lithofacies in this formation. The lithofacies of target intervals are classified into fine grained sandy debrite, silty to fine grained sandy turbidite, fine grained sandy slump, semi-deep to deep lacustrine mudstone, and deep lacustrine shale. Further, the conventional and micro-resistivity imaging log response characteristics of different lithofacies are analyzed. Compared with other lithofacies, deep lacustrine shale facies are characterized by high gamma ray (GR), high compensated neutron log (CNL), high acoustic log (AC), and low density (DEN) log values. Crossplots of GR-AC, DEN-CNL, and DEN-AC are proposed to identify most of the lithofacies, and a criterion was established for use of well logs to characterize the lithofacies. Finally, a method joining conventional logs and micro-resistivity imaging log data was applied to field wells, achieving the very high accuracy rate of 88%. The distribution maps of different lithofacies thickness in the study area are obtained. Deep lacustrine shale faces have the widest development area and many thickness centers. Accurate and effective identification of lithofacies shows that within Ordos Basin, there is an area of about 20,000 km2 with shale thickness greater than 6 m, providing an important basis for shale oil exploration in the study area.Keywords: Continental shale oil; Lithofacies; Lacustrine shale; Micro-resistivity imaging","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49654316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Oil and gas seeps have been a key tool in hydrocarbon exploration since ancient times. Basin-wide reconnaissance exploration, focused on basic geology and identification of hydrocarbon seepage, has been typical of onshore basin analysis since the beginning of the petroleum industry. Since the discovery of marine chemosynthetic cold seep communities in the mid-1980s, and their association with offshore oil and gas seepage, the energy industry has been mapping seeps both to target them for exploration and avoid them in development. For exploration, the successful sampling of oil or gas at the seafloor reduces exploration risk by demonstrating generative source rock, maturation, migration, and charge all key data about the subsurface petroleum systems. In the marine environment, seep communities and associated diagenetic precipitates can modify the bathymetry and/or the backscatter and can be imaged by Multibeam Echo Sounding (MBES). MBES can provide detailed bathymetry of the seafloor; multibeam backscatter can provide not only potential targets for seep sampling, but information on the seafloor characteristics at or just below the seafloor; and multibeam Water Column data can image gas plumes rising from the seafloor. Multibeam was introduced outside of military applications in the 1970s, with the application of multibeam to seep science in the oil and gas industry, and the use of USBL-positioned cores in a real-time GIS to target seeps, began in the late 1990s, with the first proprietary survey in 2000. We review the history of multibeam, the history of seep science, and lessons learned over decades to best practices in seep hunting, from vessel specification to dry dock to pre-survey to survey operations to target selection.
{"title":"USE OF MULTIBEAM BATHYMETRY AND BACKSCATTER TO IMPROVE SEABED GEOCHEMICAL SURVEYS: PART 1, HISTORICAL REVIEW, TECHNICAL DESCRIPTION, AND BEST PRACTICES","authors":"D. Orange, P. Teas, J. Decker, J. Gharib","doi":"10.1190/int-2021-0236.1","DOIUrl":"https://doi.org/10.1190/int-2021-0236.1","url":null,"abstract":"Oil and gas seeps have been a key tool in hydrocarbon exploration since ancient times. Basin-wide reconnaissance exploration, focused on basic geology and identification of hydrocarbon seepage, has been typical of onshore basin analysis since the beginning of the petroleum industry. Since the discovery of marine chemosynthetic cold seep communities in the mid-1980s, and their association with offshore oil and gas seepage, the energy industry has been mapping seeps both to target them for exploration and avoid them in development. For exploration, the successful sampling of oil or gas at the seafloor reduces exploration risk by demonstrating generative source rock, maturation, migration, and charge all key data about the subsurface petroleum systems. In the marine environment, seep communities and associated diagenetic precipitates can modify the bathymetry and/or the backscatter and can be imaged by Multibeam Echo Sounding (MBES). MBES can provide detailed bathymetry of the seafloor; multibeam backscatter can provide not only potential targets for seep sampling, but information on the seafloor characteristics at or just below the seafloor; and multibeam Water Column data can image gas plumes rising from the seafloor. Multibeam was introduced outside of military applications in the 1970s, with the application of multibeam to seep science in the oil and gas industry, and the use of USBL-positioned cores in a real-time GIS to target seeps, began in the late 1990s, with the first proprietary survey in 2000. We review the history of multibeam, the history of seep science, and lessons learned over decades to best practices in seep hunting, from vessel specification to dry dock to pre-survey to survey operations to target selection.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42102823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiaxue Pei, Guo Xiaoyu, Hu Yingjie, Guo Feng, Liu Baohong, Hao Liang, Zhang Ruixue, F. Zheng
With the development of wide orientation, wide band, and high-density acquisition and processing technology, the original 3D (time, line number, and track number) seismic data have expanded to two dimensions — the addition of offset distance information and azimuth information, resulting in 5D seismic data. In this paper, we explore three aspects. Identifying microfaults through subazimuth superposition and poststack coherent body techniques; predicting fractures by means of prestack anisotropy, poststack dip, azimuth, coherence, and curvature; and inscribing river channels with pure longitudinal wave near-zero incidence angle reflection information — that is, the exploration of 5D seismic prediction techniques. The field application in different types of geologic bodies in the Lujabao Depression and the Ordos Basin and the accuracy of reservoir prediction and the degree of implementation of microfaults have been greatly enhanced, effectively guiding the deployment of wells and improving the drilling success rates.
{"title":"Research and application of 5D seismic prediction technology","authors":"Jiaxue Pei, Guo Xiaoyu, Hu Yingjie, Guo Feng, Liu Baohong, Hao Liang, Zhang Ruixue, F. Zheng","doi":"10.1190/int-2021-0223.1","DOIUrl":"https://doi.org/10.1190/int-2021-0223.1","url":null,"abstract":"With the development of wide orientation, wide band, and high-density acquisition and processing technology, the original 3D (time, line number, and track number) seismic data have expanded to two dimensions — the addition of offset distance information and azimuth information, resulting in 5D seismic data. In this paper, we explore three aspects. Identifying microfaults through subazimuth superposition and poststack coherent body techniques; predicting fractures by means of prestack anisotropy, poststack dip, azimuth, coherence, and curvature; and inscribing river channels with pure longitudinal wave near-zero incidence angle reflection information — that is, the exploration of 5D seismic prediction techniques. The field application in different types of geologic bodies in the Lujabao Depression and the Ordos Basin and the accuracy of reservoir prediction and the degree of implementation of microfaults have been greatly enhanced, effectively guiding the deployment of wells and improving the drilling success rates.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41299650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Edimar Perico, H. Bedle, Bobby Buist, A. Damasceno
Seismic attributes are routinely applied for interpretation tasks. Changes in amplitude and phase components reveal faults, and provide insights into hydrocarbon reservoir management. We investigate how different seismic attributes improve the recognition of faults. Data conditioning and unsupervised machine learning methods complement the analysis. The area covered by the 4D/4C Jubarte Permanent Reservoir Monitoring (PRM) system in the northern part of Campos Basin was used to test the impact of different algorithms and parameters. Changes in seismic anomalies associated with post-salt reservoirs reveal the presence of faults and fractures. However, seismic noise and geological units with weak acoustic impedance contrasts required the application of additional methods. Spectral balancing and structure-oriented filtering (SOF) increased the lateral continuity of some stratigraphic reflectors and attenuated random noise, which improved fault surface visibility in many areas. Seismic attributes, both geometric and instantaneous, uncover additional features of fault surfaces. Comparisons between different azimuth-restricted volumes reveal that faults can be delineated when the acquisition direction is positioned perpendicular to structure. Attributes computed using the full-stack volume show less noise content and more rectilinear fault segments. Most-positive and most-negative curvature components indicate more details of major features, and have the advantage of indicating possible up-thrown and down-thrown sides of a deformational zone. The large number of seismic cubes and attributes motivated the use of principal component analysis (PCA) and self-organizing maps (SOM), which complements the identification of faults segments with clusters composed of specific neurons aligned within structural discontinuities. The improvements obtained demonstrated the importance of having a workflow that combines different methods. For the Jubarte Field, a multi-attribute approach demonstrates advantages for delineating the lateral extension of faults and a more precise discontinuity location. Finally, the impact that seismic noise and stratigraphic features may have in the characterization of discontinuities associated with faults was noted.
{"title":"Fault characterization in a postsalt reservoir interval, Juabarte Field (Campos Basin) using seismic attributes and machine learning","authors":"Edimar Perico, H. Bedle, Bobby Buist, A. Damasceno","doi":"10.1190/int-2022-0061.1","DOIUrl":"https://doi.org/10.1190/int-2022-0061.1","url":null,"abstract":"Seismic attributes are routinely applied for interpretation tasks. Changes in amplitude and phase components reveal faults, and provide insights into hydrocarbon reservoir management. We investigate how different seismic attributes improve the recognition of faults. Data conditioning and unsupervised machine learning methods complement the analysis. The area covered by the 4D/4C Jubarte Permanent Reservoir Monitoring (PRM) system in the northern part of Campos Basin was used to test the impact of different algorithms and parameters. Changes in seismic anomalies associated with post-salt reservoirs reveal the presence of faults and fractures. However, seismic noise and geological units with weak acoustic impedance contrasts required the application of additional methods. Spectral balancing and structure-oriented filtering (SOF) increased the lateral continuity of some stratigraphic reflectors and attenuated random noise, which improved fault surface visibility in many areas. Seismic attributes, both geometric and instantaneous, uncover additional features of fault surfaces. Comparisons between different azimuth-restricted volumes reveal that faults can be delineated when the acquisition direction is positioned perpendicular to structure. Attributes computed using the full-stack volume show less noise content and more rectilinear fault segments. Most-positive and most-negative curvature components indicate more details of major features, and have the advantage of indicating possible up-thrown and down-thrown sides of a deformational zone. The large number of seismic cubes and attributes motivated the use of principal component analysis (PCA) and self-organizing maps (SOM), which complements the identification of faults segments with clusters composed of specific neurons aligned within structural discontinuities. The improvements obtained demonstrated the importance of having a workflow that combines different methods. For the Jubarte Field, a multi-attribute approach demonstrates advantages for delineating the lateral extension of faults and a more precise discontinuity location. Finally, the impact that seismic noise and stratigraphic features may have in the characterization of discontinuities associated with faults was noted.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43918711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We analyzed geologic-geophysical data, both from archives and collections in recent expeditions by the Shirshov Institute of Oceanology RAS (SIO RAS), and revealed many anomalies in the seismoacoustic wavefield. Anomalies are of two types: horizontal disturbed layers and vertical pipes. Anomalies form associations — pipes (chimneys) are rooted in disturbed layers and go through sediments up to the seafloor and form pockmarks. We consider all specified seismic anomalies and bottom microrelief as a possibility of vertical migration of gas and water via sediments (fluid from sediments to water and from seawater to sediments). It is expected that the fluids form a huge underground hydrosphere below the Caspian Sea. To test the fluid flow, we made a mathematical model of fluid discharge and absorption in bottom sediments. We hypothesize that the Caspian Sea level fluctuates, at least partially, due to cycles of the submarine ground water discharge and sea water absorption back into the sediments. This cyclicity of fluid discharge and absorption correlates with regional seismic events. The earthquakes cause tectonic relaxation, triggering the absorption process, and sea-level drop due to reverse flow into sediments. In other periods, the tectonic tension causes sediment compression and fluid discharge to sea water, which causes sea-level rise. The model was tested on the recent (past 100 years) sea-level change curve. As a result, we got a distribution of the general volume of fluid flows depending on the infiltration coefficient. The real change in the Caspian Sea volume is at the lower range of the calculated values, so we cannot neglect the effect of “gas pipes” (“chimneys”) on the Caspian sea-level change.
{"title":"HIDDEN HYDROSPHERE UNDER THE CASPIAN SEA: GEOPHYSICAL EVIDENCE AND SEA LEVEL INFLUENCE","authors":"V. Putans, M. Trimonova, L. Merklin","doi":"10.1190/int-2021-0102.1","DOIUrl":"https://doi.org/10.1190/int-2021-0102.1","url":null,"abstract":"We analyzed geologic-geophysical data, both from archives and collections in recent expeditions by the Shirshov Institute of Oceanology RAS (SIO RAS), and revealed many anomalies in the seismoacoustic wavefield. Anomalies are of two types: horizontal disturbed layers and vertical pipes. Anomalies form associations — pipes (chimneys) are rooted in disturbed layers and go through sediments up to the seafloor and form pockmarks. We consider all specified seismic anomalies and bottom microrelief as a possibility of vertical migration of gas and water via sediments (fluid from sediments to water and from seawater to sediments). It is expected that the fluids form a huge underground hydrosphere below the Caspian Sea. To test the fluid flow, we made a mathematical model of fluid discharge and absorption in bottom sediments. We hypothesize that the Caspian Sea level fluctuates, at least partially, due to cycles of the submarine ground water discharge and sea water absorption back into the sediments. This cyclicity of fluid discharge and absorption correlates with regional seismic events. The earthquakes cause tectonic relaxation, triggering the absorption process, and sea-level drop due to reverse flow into sediments. In other periods, the tectonic tension causes sediment compression and fluid discharge to sea water, which causes sea-level rise. The model was tested on the recent (past 100 years) sea-level change curve. As a result, we got a distribution of the general volume of fluid flows depending on the infiltration coefficient. The real change in the Caspian Sea volume is at the lower range of the calculated values, so we cannot neglect the effect of “gas pipes” (“chimneys”) on the Caspian sea-level change.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44127915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ruiqiang Yang, W. Ding, Zhan Zhao, Jingtao Liu, Shuo Shi, Teng Zhao, Peng Han
With increasing oil and gas exploration and development, well trajectory optimization has gradually become the focus of the oil and gas industry. Considering the wellbore instability in the Shunbei area of the Tarim Basin, the well trajectory was scientifically optimized under the guidance of rock mechanics, drilling engineering, and mathematical methods, combined with actual geologic data, and with in situ stress as the main controlling factor. In this paper, the stress state of the wellbore is analyzed by linear elastic theory to establish the stress distribution model of the wellbore. The safety window model of wellbore stability is established using different rock failure criteria to calculate the collapse pressure and fracture pressure of the formation. Based on this, the safe mud density window is defined to achieve wellbore trajectory optimization. Finally, the influence factors of wellbore stability are discussed, and the applicability of different rock failure criteria is evaluated. The results indicate that under the normal faulting stress regime condition in the study area, the direction of horizontal minimum principal stress is the best drilling direction, where the borehole inclination angle of α > 50° is the optimal well trajectory. The wellbore stabilities of high-angle deviated wells and horizontal wells are better than those of low-angle deviated wells and vertical wells. The calculation results of the Mogi-Coulomb criterion can describe the conditions of the in situ stress field more accurately. The safe windows for different well trajectories are obtained directly by the numerical method, which is very practical for optimizing well trajectories and improving wellbore stability.
{"title":"Well trajectory optimization of ultra-deep and high-pressure drilling engineering based on high in-situ stress as the main control factor: a case study from the Ordovician carbonated reservoir in Shunbei area of Tarim basin","authors":"Ruiqiang Yang, W. Ding, Zhan Zhao, Jingtao Liu, Shuo Shi, Teng Zhao, Peng Han","doi":"10.1190/int-2022-0058.1","DOIUrl":"https://doi.org/10.1190/int-2022-0058.1","url":null,"abstract":"With increasing oil and gas exploration and development, well trajectory optimization has gradually become the focus of the oil and gas industry. Considering the wellbore instability in the Shunbei area of the Tarim Basin, the well trajectory was scientifically optimized under the guidance of rock mechanics, drilling engineering, and mathematical methods, combined with actual geologic data, and with in situ stress as the main controlling factor. In this paper, the stress state of the wellbore is analyzed by linear elastic theory to establish the stress distribution model of the wellbore. The safety window model of wellbore stability is established using different rock failure criteria to calculate the collapse pressure and fracture pressure of the formation. Based on this, the safe mud density window is defined to achieve wellbore trajectory optimization. Finally, the influence factors of wellbore stability are discussed, and the applicability of different rock failure criteria is evaluated. The results indicate that under the normal faulting stress regime condition in the study area, the direction of horizontal minimum principal stress is the best drilling direction, where the borehole inclination angle of α > 50° is the optimal well trajectory. The wellbore stabilities of high-angle deviated wells and horizontal wells are better than those of low-angle deviated wells and vertical wells. The calculation results of the Mogi-Coulomb criterion can describe the conditions of the in situ stress field more accurately. The safe windows for different well trajectories are obtained directly by the numerical method, which is very practical for optimizing well trajectories and improving wellbore stability.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44660628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High porosity but low-production wells exist in the Leikoupo Formation in the Sichuan Basin, China. The unclear explanation for this phenomenon has led to the failure of fracture development. We selected 15 cores from the study area based on the oil test data to investigate the cause from the pore structure perspective. The pore structures were studied via a variety of petrophysical experiments, which include conventional physical property analysis, casting thin section, nuclear magnetic resonance technique, and constant-rate mercury injection. The results indicate that the main explanation for the high porosity but low-production wells is that the larger pore-to-throat ratio makes for poor pore connectivity and more large pores and vugs are trapped. Movable fluid saturation can be significantly influenced by microscopic pore structure rather than physical parameters, which is positively affected by throat radius and negatively correlated with the pore-throat radius ratio, relative sorting coefficient, and tortuosity of the throat. The results provide a basis for the exploration of carbonate reservoirs from a microscopic perspective.
{"title":"Why high porosity but low production wells occur in carbonate reservoirs: An explanation from the perspective of pore structure","authors":"Fengjiao Zhang, S. Deng, Xuechun Wang, Li Bai","doi":"10.1190/int-2022-0029.1","DOIUrl":"https://doi.org/10.1190/int-2022-0029.1","url":null,"abstract":"High porosity but low-production wells exist in the Leikoupo Formation in the Sichuan Basin, China. The unclear explanation for this phenomenon has led to the failure of fracture development. We selected 15 cores from the study area based on the oil test data to investigate the cause from the pore structure perspective. The pore structures were studied via a variety of petrophysical experiments, which include conventional physical property analysis, casting thin section, nuclear magnetic resonance technique, and constant-rate mercury injection. The results indicate that the main explanation for the high porosity but low-production wells is that the larger pore-to-throat ratio makes for poor pore connectivity and more large pores and vugs are trapped. Movable fluid saturation can be significantly influenced by microscopic pore structure rather than physical parameters, which is positively affected by throat radius and negatively correlated with the pore-throat radius ratio, relative sorting coefficient, and tortuosity of the throat. The results provide a basis for the exploration of carbonate reservoirs from a microscopic perspective.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48828211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuping Wu, Chenglin Liu, F. Jiang, T. Hu, Chenxi Zhang, Jiahao Lv, M. Hu, Renda Huang, Guanyun Wu, Rizwan Sarwar Awan
The Permian source rocks in the Junggar Basin are widely developed, especially the Fengcheng Formation, which is the most significant source rock in the basin. However, due to insufficient research on the hydrocarbon generation (HG) and hydrocarbon expulsion (HE) characteristics of the source rocks, it is unclear whether a significant amount of retained hydrocarbons remain within shales. In general, the original organic matter abundance and kerogen type control hydrocarbon generation potential (HGP) and HE capacity in lacustrine shales. Therefore, the degradation rate method was used to establish the original organic carbon recovery model for different types of kerogen. Combined with the geologic and geochemical characteristics of the source rock, the HG, HE, and shale oil resource potential of the Fengcheng shale have been evaluated. We have found that the Fengcheng shale is mainly carbonate-type mudstone widely distributed with an average thickness greater than 100 m. The Fengcheng shale is composed of type II kerogen and reached the mature to high-mature thermal maturity stage, with the maximum original organic carbon exceeding 4.0 wt%. Meanwhile, the amount of retained hydrocarbons within shales is abundant according to the HGP model. Monte Carlo simulation finds that the shale oil resources of the Fengcheng shale are 23.30 × 108 t. Free oil resources account for 60%, reaching 13.75 × 108 t, indicating tremendous shale oil exploration potential.
{"title":"Hydrocarbon generation and expulsion of Fengcheng Formation in the Mahu Sag, Junggar Basin, China: Implication for shale oil resource potential","authors":"Yuping Wu, Chenglin Liu, F. Jiang, T. Hu, Chenxi Zhang, Jiahao Lv, M. Hu, Renda Huang, Guanyun Wu, Rizwan Sarwar Awan","doi":"10.1190/int-2022-0060.1","DOIUrl":"https://doi.org/10.1190/int-2022-0060.1","url":null,"abstract":"The Permian source rocks in the Junggar Basin are widely developed, especially the Fengcheng Formation, which is the most significant source rock in the basin. However, due to insufficient research on the hydrocarbon generation (HG) and hydrocarbon expulsion (HE) characteristics of the source rocks, it is unclear whether a significant amount of retained hydrocarbons remain within shales. In general, the original organic matter abundance and kerogen type control hydrocarbon generation potential (HGP) and HE capacity in lacustrine shales. Therefore, the degradation rate method was used to establish the original organic carbon recovery model for different types of kerogen. Combined with the geologic and geochemical characteristics of the source rock, the HG, HE, and shale oil resource potential of the Fengcheng shale have been evaluated. We have found that the Fengcheng shale is mainly carbonate-type mudstone widely distributed with an average thickness greater than 100 m. The Fengcheng shale is composed of type II kerogen and reached the mature to high-mature thermal maturity stage, with the maximum original organic carbon exceeding 4.0 wt%. Meanwhile, the amount of retained hydrocarbons within shales is abundant according to the HGP model. Monte Carlo simulation finds that the shale oil resources of the Fengcheng shale are 23.30 × 108 t. Free oil resources account for 60%, reaching 13.75 × 108 t, indicating tremendous shale oil exploration potential.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66168824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reservoir facies studies are of great importance in different stages of exploration and development of hydrocarbon fields. We have aimed to generate a reservoir facies model for the Asmari Formation in an onshore oil field located southwest of Iran. Input data for electrofacies (EF) clustering algorithms are used, which include gamma-ray (GR), density (RHOB), porosity, and sonic logs from four wells. We obtain the petrophysical group (PG) and EF class using core data (mercury injection capillary pressure) and well-logs analysis. The integration of PGs and log EF significantly decreases the uncertainty in reservoir modeling, which alternatively enhances field development decisions. We compare the multiresolution graph-based clustering (MRGC) and k-means clustering methods. EF clustering results find nine EF classes. We delineate high-quality reservoirs based on lower GR, RHOB, and high-porosity logs. Next, we use the clustering results in the static reservoir modeling process, using the sequential index simulation and indicator kriging methods. The comparison between the facies obtained models and existing drilling core data finds that the absolute percentage error of the MRGC algorithm is less than that of the k-means algorithm. The results obtained by this study can provide useful information for the development of hydrocarbon exploration plans in the studied oil field.
{"title":"Integrating facies analysis and geostatistical methods in an onshore oil field using petrophysical groups","authors":"Neamatullah Mohammed Rashid, M. Riahi","doi":"10.1190/int-2022-0010.1","DOIUrl":"https://doi.org/10.1190/int-2022-0010.1","url":null,"abstract":"Reservoir facies studies are of great importance in different stages of exploration and development of hydrocarbon fields. We have aimed to generate a reservoir facies model for the Asmari Formation in an onshore oil field located southwest of Iran. Input data for electrofacies (EF) clustering algorithms are used, which include gamma-ray (GR), density (RHOB), porosity, and sonic logs from four wells. We obtain the petrophysical group (PG) and EF class using core data (mercury injection capillary pressure) and well-logs analysis. The integration of PGs and log EF significantly decreases the uncertainty in reservoir modeling, which alternatively enhances field development decisions. We compare the multiresolution graph-based clustering (MRGC) and k-means clustering methods. EF clustering results find nine EF classes. We delineate high-quality reservoirs based on lower GR, RHOB, and high-porosity logs. Next, we use the clustering results in the static reservoir modeling process, using the sequential index simulation and indicator kriging methods. The comparison between the facies obtained models and existing drilling core data finds that the absolute percentage error of the MRGC algorithm is less than that of the k-means algorithm. The results obtained by this study can provide useful information for the development of hydrocarbon exploration plans in the studied oil field.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66168663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An attractive feature seen on seismic data, also known as funny-looking thing or FLT, henceforth has a wide range of interpretations, from noise patterns to amplitude anomalies. An example of an FLT is the similar faulting patterns between a volcanic intrusion and a salt intrusion from the point of view of a machine learning (ML) algorithm. Oftentimes, seismic interpreters do not have a complete data set or geologic background to determine the genesis of the observed features. This can be particularly perplexing when trying to determine if an intrusion is volcanic or halokinetic in origin because they exhibit similar geomorphologies. We examine the differences in these features in the Gulf of Mexico, which is a well-documented salt basin, and the Taranaki Basin in New Zealand, which is igneous prone. The analysis aims to discern geologic features based on the geometries and attributes shared by seismic data and remote sensing tools. Seismic attributes and ML techniques highlight differences and similarities between the intrusions. We discuss ML techniques, such as self-organized maps (SOMs), an unsupervised ML technique, and cluster fault systems without regard to the geologic context. The attributes used in the SOM are fault probability, fault dip azimuth, fault dip magnitude, and thin-bed detector. Fault probability is performed through a combination of convolutional neural network fault prediction and a skeletonization process. Once the faults are clustered using SOM, the visualization of fault architecture due to the existing mount (either volcano or salt dome) is done considering high fault probabilities (>75%). The methodology consists of selecting the neurons from the SOM grid corresponding to the presence of faults and combining them with fault probability and a fault dip azimuth using a crossplot. The crossplot product assists in the automatic extraction of the fault planes using: (1) a voxel representation of the fault planes and (2) fault patches representing the fault planes. Moreover, the visualization technique defined demonstrates that the crossplot product yields better-defined fault planes. With the fault system characterized, we compare horizon slices using coherence, fault dip magnitude, and azimuth against remote sensing images with similar attributes. In conclusion, our methodology combines technologies to differentiate the genesis of intrusion — salt or igneous — using the fault presence and could be helpful in frontier exploration or planetary exploration.
{"title":"Contrasting faulting styles of salt domes and volcanos: Can unsupervised learning techniques differentiate similar fault styles?","authors":"Alexandro Vera-Arroyo, H. Bedle","doi":"10.1190/int-2022-0018.1","DOIUrl":"https://doi.org/10.1190/int-2022-0018.1","url":null,"abstract":"An attractive feature seen on seismic data, also known as funny-looking thing or FLT, henceforth has a wide range of interpretations, from noise patterns to amplitude anomalies. An example of an FLT is the similar faulting patterns between a volcanic intrusion and a salt intrusion from the point of view of a machine learning (ML) algorithm. Oftentimes, seismic interpreters do not have a complete data set or geologic background to determine the genesis of the observed features. This can be particularly perplexing when trying to determine if an intrusion is volcanic or halokinetic in origin because they exhibit similar geomorphologies. We examine the differences in these features in the Gulf of Mexico, which is a well-documented salt basin, and the Taranaki Basin in New Zealand, which is igneous prone. The analysis aims to discern geologic features based on the geometries and attributes shared by seismic data and remote sensing tools. Seismic attributes and ML techniques highlight differences and similarities between the intrusions. We discuss ML techniques, such as self-organized maps (SOMs), an unsupervised ML technique, and cluster fault systems without regard to the geologic context. The attributes used in the SOM are fault probability, fault dip azimuth, fault dip magnitude, and thin-bed detector. Fault probability is performed through a combination of convolutional neural network fault prediction and a skeletonization process. Once the faults are clustered using SOM, the visualization of fault architecture due to the existing mount (either volcano or salt dome) is done considering high fault probabilities (>75%). The methodology consists of selecting the neurons from the SOM grid corresponding to the presence of faults and combining them with fault probability and a fault dip azimuth using a crossplot. The crossplot product assists in the automatic extraction of the fault planes using: (1) a voxel representation of the fault planes and (2) fault patches representing the fault planes. Moreover, the visualization technique defined demonstrates that the crossplot product yields better-defined fault planes. With the fault system characterized, we compare horizon slices using coherence, fault dip magnitude, and azimuth against remote sensing images with similar attributes. In conclusion, our methodology combines technologies to differentiate the genesis of intrusion — salt or igneous — using the fault presence and could be helpful in frontier exploration or planetary exploration.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46802741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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