Very high concentrations of CO2 have been encountered in solution as carbonic acid in hydrocarbon reservoirs in parts of the Greater Sarawak Basin, offshore Borneo, Malaysia. Concentrations can exceed 80%. Anomalous features in 3D seismic data also are found in areas with high CO2 concentrations. These features appear as halos around reservoirs, cutting across stratigraphy and indicating a hardening of the nonreservoir rocks within the envelope of the halo. These halos can extend for hundreds of meters above and below a reservoir. Elastic log data from wells that pass through and adjacent to these seismic anomalies indicate that mudrocks within the anomalies have higher densities and velocities than would be predicted from locally derived compaction trends. Combinable magnetic resonance measurements indicate that the anomalous properties are the result of lower-than-expected capillary-bound microporosities. It is proposed that carbonic acid in the reservoir fluids diffuses into the bounding rocks, causing a loss of porosity. The amount of porosity lost depends on the clay content of the mudrock and the initial level of compaction, with shallower, more clay-rich shales able to lose more porosity. The anomalous seismic signatures result from a sharp transition (over approximately 5 m) at the diagenetic front between normal and altered rocks. The alteration can significantly change the amplitude variation with offset response of the reservoirs and therefore the ability to correctly predict fluid phase and reservoir quality. No anomalies are observed when the concentration of CO2 in the reservoir is less than 10% but always present when CO2 exceeds 20%. Therefore, it is possible to map the general distribution of high CO2 concentration from seismic data. There is no indication that the scale, amplitude, or shape of the anomalies gives an indication of the concentration of CO2.
{"title":"Anomalous elastic properties of mudrocks bounding reservoirs with high concentrations of naturally occurring CO2","authors":"M. Sams, T. Jayasangar","doi":"10.1190/int-2022-0115.1","DOIUrl":"https://doi.org/10.1190/int-2022-0115.1","url":null,"abstract":"Very high concentrations of CO2 have been encountered in solution as carbonic acid in hydrocarbon reservoirs in parts of the Greater Sarawak Basin, offshore Borneo, Malaysia. Concentrations can exceed 80%. Anomalous features in 3D seismic data also are found in areas with high CO2 concentrations. These features appear as halos around reservoirs, cutting across stratigraphy and indicating a hardening of the nonreservoir rocks within the envelope of the halo. These halos can extend for hundreds of meters above and below a reservoir. Elastic log data from wells that pass through and adjacent to these seismic anomalies indicate that mudrocks within the anomalies have higher densities and velocities than would be predicted from locally derived compaction trends. Combinable magnetic resonance measurements indicate that the anomalous properties are the result of lower-than-expected capillary-bound microporosities. It is proposed that carbonic acid in the reservoir fluids diffuses into the bounding rocks, causing a loss of porosity. The amount of porosity lost depends on the clay content of the mudrock and the initial level of compaction, with shallower, more clay-rich shales able to lose more porosity. The anomalous seismic signatures result from a sharp transition (over approximately 5 m) at the diagenetic front between normal and altered rocks. The alteration can significantly change the amplitude variation with offset response of the reservoirs and therefore the ability to correctly predict fluid phase and reservoir quality. No anomalies are observed when the concentration of CO2 in the reservoir is less than 10% but always present when CO2 exceeds 20%. Therefore, it is possible to map the general distribution of high CO2 concentration from seismic data. There is no indication that the scale, amplitude, or shape of the anomalies gives an indication of the concentration of CO2.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46284870","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}
Unique lacustrine mixed siliciclastic-carbonate sedimentary rocks accumulated during deposition of the second member of the Paleogene Funing Formation in the Jinhu Sag and Gaoyou Sag, Subei Basin, which has significant scientific and petroleum exploration values. The reservoir characteristics of the deposits were summarized by means of core observation, petrographic analyses, scanning electron microscope analysis, porosity and permeability tests, carbonate content measurement and X-ray diffraction clay mineral analyses. These special deposits consisting of siliciclastics and allochems were mainly found in a shallow lake at the front and side of deltas, and were also found in gravity flow deposits of a deep lake. The results show that lithology and dissolution of early calcite cements together influence the reservoir performance. From a sedimentological perspective, two types of lacustrine deposits are present in the study area. The first one preserves massive or graded bedding composed of allochems (ooids and intraclasts) and siliciclastics (mainly quartz) of various grain sizes, as well as marl; this type of reservoir is poorly sorted. The second one preserves wavy cross-lamination composed of ooids and quartz of similar size; this type of reservoir is well sorted. The diagenesis of reservoirs in the study area mainly includes compaction, cementation and dissolution. Reservoirs with massive or graded bedding were impacted by compaction, with current porosity less than 5%. Reservoirs with wavy cross-lamination could form high-quality reservoirs with porosity up to 22%, in which secondary dissolution pores represent the main type of porosity. The early calcite cementation may have inhibited compaction prior to the formation of solution vugs and the formation of high-quality reservoirs.
{"title":"Reservoir characteristics of lacustrine mixed siliciclastic-carbonate sedimentary rocks: A case study of the Paleogene Funing 2lt;supgt;ndlt;/supgt; Member in Subei Basin, China","authors":"Wei Li, Xiaomin Zhu, Qidong Liu","doi":"10.1190/int-2022-0044.1","DOIUrl":"https://doi.org/10.1190/int-2022-0044.1","url":null,"abstract":"Unique lacustrine mixed siliciclastic-carbonate sedimentary rocks accumulated during deposition of the second member of the Paleogene Funing Formation in the Jinhu Sag and Gaoyou Sag, Subei Basin, which has significant scientific and petroleum exploration values. The reservoir characteristics of the deposits were summarized by means of core observation, petrographic analyses, scanning electron microscope analysis, porosity and permeability tests, carbonate content measurement and X-ray diffraction clay mineral analyses. These special deposits consisting of siliciclastics and allochems were mainly found in a shallow lake at the front and side of deltas, and were also found in gravity flow deposits of a deep lake. The results show that lithology and dissolution of early calcite cements together influence the reservoir performance. From a sedimentological perspective, two types of lacustrine deposits are present in the study area. The first one preserves massive or graded bedding composed of allochems (ooids and intraclasts) and siliciclastics (mainly quartz) of various grain sizes, as well as marl; this type of reservoir is poorly sorted. The second one preserves wavy cross-lamination composed of ooids and quartz of similar size; this type of reservoir is well sorted. The diagenesis of reservoirs in the study area mainly includes compaction, cementation and dissolution. Reservoirs with massive or graded bedding were impacted by compaction, with current porosity less than 5%. Reservoirs with wavy cross-lamination could form high-quality reservoirs with porosity up to 22%, in which secondary dissolution pores represent the main type of porosity. The early calcite cementation may have inhibited compaction prior to the formation of solution vugs and the formation of high-quality reservoirs.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43603532","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}
Cross-well strain measurements using Low-frequency Distributed Acoustic Sensing (LF-DAS) is an emerging technique to monitor hydraulic fracture propagation. The qualitative interpretations of the strain rate data have been used to evaluate the fracturing stimulation efficiency, hydraulic fracture geometry, and cross-well communication. Limited studies have investigated the cross-well strain signals recorded from offset fibers during zipper fracturing treatment, though zipper fracturing becomes a routine method of stimulating horizontal wells in unconventional reservoirs. This gap will be filled in this research by presenting the methods we developed to investigate complicated LF-DAS signals. These approaches were further demonstrated using field datasets recorded along the two temporal sensing fiber cables during the zipper fracturing operation of seven offset wells with two fracking crews operating simultaneously. By exploring, comparing, and presenting the LF-DAS data recorded in wireline and disposable fiber cables, this research shares the best practices for visualizing and interpreting cross-well strain signals. The LF-DAS dataset shown in this study, which, to the best of our knowledge, is one of the most complicated LF-DAS datasets presented. The approaches proposed here can be extended and applied to visualize and interpret different kinds of complicated LF-DAS signals recorded using permanent, wireline, and disposable fiber cables.
{"title":"Challenges and Best Practices in Interpreting Cross-well Strain Signals to Monitor Multi-Crew Zipper Fracturing Operations","authors":"Yanrui Ning, G. Jin","doi":"10.1190/int-2022-0092.1","DOIUrl":"https://doi.org/10.1190/int-2022-0092.1","url":null,"abstract":"Cross-well strain measurements using Low-frequency Distributed Acoustic Sensing (LF-DAS) is an emerging technique to monitor hydraulic fracture propagation. The qualitative interpretations of the strain rate data have been used to evaluate the fracturing stimulation efficiency, hydraulic fracture geometry, and cross-well communication. Limited studies have investigated the cross-well strain signals recorded from offset fibers during zipper fracturing treatment, though zipper fracturing becomes a routine method of stimulating horizontal wells in unconventional reservoirs. This gap will be filled in this research by presenting the methods we developed to investigate complicated LF-DAS signals. These approaches were further demonstrated using field datasets recorded along the two temporal sensing fiber cables during the zipper fracturing operation of seven offset wells with two fracking crews operating simultaneously. By exploring, comparing, and presenting the LF-DAS data recorded in wireline and disposable fiber cables, this research shares the best practices for visualizing and interpreting cross-well strain signals. The LF-DAS dataset shown in this study, which, to the best of our knowledge, is one of the most complicated LF-DAS datasets presented. The approaches proposed here can be extended and applied to visualize and interpret different kinds of complicated LF-DAS signals recorded using permanent, wireline, and disposable fiber cables.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42876912","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}
Accurate knowledge of fracture extents generated in multistage unconventional completions remains elusive. Crosswell low-frequency distributed acoustic sensing (LF-DAS) measurements can determine the time and location of a frac hit. Knowing where and when a frac hit occurs constrains the fracture extent but does not estimate it quantitatively. A recent study on crosswell LF-DAS demonstrated a simple method to rapidly determine the instantaneous fracture propagation rate when a frac hit occurs. This method, the zero strain rate location method (ZSRLM), is based on laboratory experiments and numerical modeling assuming a radial fracture geometry. An estimated fracture propagation velocity can be used to extrapolate a final fracture extent. The propagation rate is calculated based on dynamic estimates of the nearest distance from the fiber to the front of a propagating fracture.In this work, the ZSRLM is adapted to estimate the distance to the fracture front based on rectangular fracture geometries. A three-dimensional displacement discontinuity method program generates crosswell LF-DAS strain rate waterfall plots considering a single, rectangular fracture of constant height. Over thirty different simulations were conducted varying formation mechanical properties, fracture height, and the vertical and horizontal offset between the treatment and monitor well. For each simulated case, the ZSRLM is used to estimate the distance to the fracture front based on the simulated waterfall plots. The difference between the estimated and actual distance to the front is minimized by a shape factor. The relationship between the shape factor, fracture height ratio, and vertical offset ratio is determined. Using a shape factor improves the performance of the ZSRLM by up to a factor of two for rectangular fractures. The updated ZSRLM is applied to extrapolate final fracture extents in two field cases: a single cluster stage in the Montney formation and a multi-cluster stage of an Austin Chalk completion.
{"title":"Low-frequency distributed acoustic sensing shape factors for fracture front detection","authors":"S. Leggett","doi":"10.1190/int-2022-0100.1","DOIUrl":"https://doi.org/10.1190/int-2022-0100.1","url":null,"abstract":"Accurate knowledge of fracture extents generated in multistage unconventional completions remains elusive. Crosswell low-frequency distributed acoustic sensing (LF-DAS) measurements can determine the time and location of a frac hit. Knowing where and when a frac hit occurs constrains the fracture extent but does not estimate it quantitatively. A recent study on crosswell LF-DAS demonstrated a simple method to rapidly determine the instantaneous fracture propagation rate when a frac hit occurs. This method, the zero strain rate location method (ZSRLM), is based on laboratory experiments and numerical modeling assuming a radial fracture geometry. An estimated fracture propagation velocity can be used to extrapolate a final fracture extent. The propagation rate is calculated based on dynamic estimates of the nearest distance from the fiber to the front of a propagating fracture.In this work, the ZSRLM is adapted to estimate the distance to the fracture front based on rectangular fracture geometries. A three-dimensional displacement discontinuity method program generates crosswell LF-DAS strain rate waterfall plots considering a single, rectangular fracture of constant height. Over thirty different simulations were conducted varying formation mechanical properties, fracture height, and the vertical and horizontal offset between the treatment and monitor well. For each simulated case, the ZSRLM is used to estimate the distance to the fracture front based on the simulated waterfall plots. The difference between the estimated and actual distance to the front is minimized by a shape factor. The relationship between the shape factor, fracture height ratio, and vertical offset ratio is determined. Using a shape factor improves the performance of the ZSRLM by up to a factor of two for rectangular fractures. The updated ZSRLM is applied to extrapolate final fracture extents in two field cases: a single cluster stage in the Montney formation and a multi-cluster stage of an Austin Chalk completion.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49301845","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}
Compared with conventional geophone data, distributed fiber-optic sensing, including distributed acoustic sensing (DAS), can provide better spatial coverage for imaging the subsurface with finer spatial sampling. Because DAS measures subsurface seismic responses differently than the geophone, imaging technologies (e.g., reverse time migration and full-waveform inversion) that are developed for conventional geophone data cannot be readily applied to original DAS data without causing uncertainties in phase or depth, especially when one compares the DAS imaging results against the usual geophone imaging results. Based on vertical seismic profile field data from a CO2 sequestration site, we have compared the imaging results of the CO2 storage reservoir associated with the DAS and the geophone data, respectively, and we illustrate the differences between the imaging results of the DAS and geophone data. The difference between the DAS and geophone imaging results could be critical in obtaining time-lapse signals for monitoring reservoir changes, e.g., in subsurface CO2 sequestration. We develop to convert DAS to geophone data so that we can reduce the discrepancies between DAS and geophone imaging results and we therefore can reuse existing seismic imaging technologies. Two conversion methods, one physics-based and one deep-learning (DL)-based, are used for the DAS-to-geophone transformation. Field data results demonstrate that the DL-based approach can better successfully improve the alignment between the DAS and geophone images, whereas the physics-based solution is constrained by its assumption.
{"title":"Imaging distributed acoustic sensing-to-geophone conversion data: A field application to CO2 sequestration data","authors":"Yong Ma, Lei Fu, Weichang Li","doi":"10.1190/int-2022-0098.1","DOIUrl":"https://doi.org/10.1190/int-2022-0098.1","url":null,"abstract":"Compared with conventional geophone data, distributed fiber-optic sensing, including distributed acoustic sensing (DAS), can provide better spatial coverage for imaging the subsurface with finer spatial sampling. Because DAS measures subsurface seismic responses differently than the geophone, imaging technologies (e.g., reverse time migration and full-waveform inversion) that are developed for conventional geophone data cannot be readily applied to original DAS data without causing uncertainties in phase or depth, especially when one compares the DAS imaging results against the usual geophone imaging results. Based on vertical seismic profile field data from a CO2 sequestration site, we have compared the imaging results of the CO2 storage reservoir associated with the DAS and the geophone data, respectively, and we illustrate the differences between the imaging results of the DAS and geophone data. The difference between the DAS and geophone imaging results could be critical in obtaining time-lapse signals for monitoring reservoir changes, e.g., in subsurface CO2 sequestration. We develop to convert DAS to geophone data so that we can reduce the discrepancies between DAS and geophone imaging results and we therefore can reuse existing seismic imaging technologies. Two conversion methods, one physics-based and one deep-learning (DL)-based, are used for the DAS-to-geophone transformation. Field data results demonstrate that the DL-based approach can better successfully improve the alignment between the DAS and geophone images, whereas the physics-based solution is constrained by its assumption.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43441499","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}
Seismic-reflection data contain residual noise after processing, which can cause geologic misinterpretation of noise-sensitive seismic attributes. For detailed subsurface imaging, seismic data conditioning can enhance the visualization of subsurface reflection features down to the limit of seismic resolution. This study on the Gabes-Tripoli Basin of western offshore Libya demonstrates the potential of postprocessing seismic data conditioning using a standard industry 3D-seismic data set. The seismic data exhibit distinct reflection discontinuities and configurations interpreted as folds, reverse faults, and crustal- and gravity-driven normal faults. Other reflection discontinuities are interpreted as imaging the external form and internal architecture of buried carbonate platforms. The seismic-reflection interpretation finds that seismic data conditioning by filtering strongly supports the interpretation of the 3D geometry, type, and trend of distinct subsurface reflection features, particularly if used as input for a structural-attribute generation. Postprocessing seismic conditioning initially improved the signal-to-noise ratio by structure-oriented filtering with edge preservation. Application of this filter configuration emphasized subtle geologic features supporting, e.g., the detection of faults close to the limit of the seismic resolution. At the same time, the filtering resulted in a higher lateral continuity of the individual seismic reflectors, supporting the autotracking of the horizons. Structural attributes generated from the conditioned data such as the variance and curvature imaged more subsurface reflection detail when compared with the structural attributes generated from nonconditioned data. The filter-based workflow proposed can be applied in most seismic interpretation software packages and is recommended to be used as a standard procedure preceding a structure-attribute calculation and structural interpretation of the seismic-reflection data of limited quality.
{"title":"Visualizing subtle structural and stratigraphic features on 3D seismic-reflection data: a case study from offshore Libya","authors":"Nabil Khalifa, S. Back","doi":"10.1190/int-2022-0056.1","DOIUrl":"https://doi.org/10.1190/int-2022-0056.1","url":null,"abstract":"Seismic-reflection data contain residual noise after processing, which can cause geologic misinterpretation of noise-sensitive seismic attributes. For detailed subsurface imaging, seismic data conditioning can enhance the visualization of subsurface reflection features down to the limit of seismic resolution. This study on the Gabes-Tripoli Basin of western offshore Libya demonstrates the potential of postprocessing seismic data conditioning using a standard industry 3D-seismic data set. The seismic data exhibit distinct reflection discontinuities and configurations interpreted as folds, reverse faults, and crustal- and gravity-driven normal faults. Other reflection discontinuities are interpreted as imaging the external form and internal architecture of buried carbonate platforms. The seismic-reflection interpretation finds that seismic data conditioning by filtering strongly supports the interpretation of the 3D geometry, type, and trend of distinct subsurface reflection features, particularly if used as input for a structural-attribute generation. Postprocessing seismic conditioning initially improved the signal-to-noise ratio by structure-oriented filtering with edge preservation. Application of this filter configuration emphasized subtle geologic features supporting, e.g., the detection of faults close to the limit of the seismic resolution. At the same time, the filtering resulted in a higher lateral continuity of the individual seismic reflectors, supporting the autotracking of the horizons. Structural attributes generated from the conditioned data such as the variance and curvature imaged more subsurface reflection detail when compared with the structural attributes generated from nonconditioned data. The filter-based workflow proposed can be applied in most seismic interpretation software packages and is recommended to be used as a standard procedure preceding a structure-attribute calculation and structural interpretation of the seismic-reflection data of limited quality.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48034054","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}
The Archie model is the foundation for calculating oil saturation, but limitations exist when the model is used to calculate oil saturation in water-flooded layer. In the process of water injection, the dynamic change in oil saturation will be caused by the different degrees of water flooding and the properties of the injected water. Under the dynamic condition of water flooding, the Archie model is not suitable for calculating the oil saturation of water flooded layers. By combining dynamic and static methods, a "double ratio" model of the same sedimentary facies layer in the later development stage was established: Rt = R0− R0· f( Fw)=R0[1− f( Fw)]. Based on the parameters of rock resistivity and formation water resistivity, an improved Archie model for calculating oil saturation in water flooded layers of the same sedimentary facies was established. The interpretation of the actual data of the Zhenwu Oilfield in Jiangsu, China shows that the average relative error between the calculation result and the core analysis result is 5.46%. The calculation result is reasonable, which offers a scientific basis for predicting the remaining oil distributions. The computational results have been validated by real datasets. This improved mode can provide experience-based guidance for the calculation of the remaining oil saturation of the water flooded layer in the same sedimentary interpretation layer.
{"title":"Calculation of oil saturation in water-flooded layers based on the modified Archie model","authors":"Xiaodong Zhao, Weilong Wang, Qi Li, Guinan Zhen, Boyu Zhou, Beibei Liu, Jiamin Qin, Yaxuan Zhang","doi":"10.1190/int-2022-0036.1","DOIUrl":"https://doi.org/10.1190/int-2022-0036.1","url":null,"abstract":"The Archie model is the foundation for calculating oil saturation, but limitations exist when the model is used to calculate oil saturation in water-flooded layer. In the process of water injection, the dynamic change in oil saturation will be caused by the different degrees of water flooding and the properties of the injected water. Under the dynamic condition of water flooding, the Archie model is not suitable for calculating the oil saturation of water flooded layers. By combining dynamic and static methods, a \"double ratio\" model of the same sedimentary facies layer in the later development stage was established: Rt = R0− R0· f( Fw)=R0[1− f( Fw)]. Based on the parameters of rock resistivity and formation water resistivity, an improved Archie model for calculating oil saturation in water flooded layers of the same sedimentary facies was established. The interpretation of the actual data of the Zhenwu Oilfield in Jiangsu, China shows that the average relative error between the calculation result and the core analysis result is 5.46%. The calculation result is reasonable, which offers a scientific basis for predicting the remaining oil distributions. The computational results have been validated by real datasets. This improved mode can provide experience-based guidance for the calculation of the remaining oil saturation of the water flooded layer in the same sedimentary interpretation layer.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44542920","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}
Borehole image logs greatly facilitate detailed characterization of rock formations, especially for the highly heterogeneous and anisotropic carbonate rocks. However, interpreting image logs requires massive time and workforce and lacks consistency and repeatability because it relies heavily on a human interpreter's expertise, experience, and alertness. Thus, we propose to train an end-to-end deep neural network (DNN) for instant and consistent facies classification of carbonate rocks from acoustic image logs and gamma ray logs. The DNN is modified from the well-known U-Net for image segmentation. The training data are composed of two datasets: (1) manually labeled field data measured by different imaging tools from the geologically complex Brazilian pre-salt region and (2) noise-free synthetic data. Some short sections of the field data that are challenging for manual labeling due to entangled features and noises or low resolution are left unlabeled for a blind test after training. All labeled data are divided into a training set, a validation set, and a test set to avoid over-fitting. We demonstrate that the trained DNN achieves 77% classification accuracy for the test set and provides reasonable predictions for the challenging unlabeled sets. It is a great achievement given the complexity and variability of the field data. Compared with manual classification, our DNN provides more consistent and higher-resolution predictions in a highly efficient manner and thus dramatically contributes to automatic image log interpretation.
{"title":"Automatic facies classification from acoustic image logs using deep neural networks","authors":"Nan You, Elita Li, Arthur Cheng","doi":"10.1190/int-2022-0069.1","DOIUrl":"https://doi.org/10.1190/int-2022-0069.1","url":null,"abstract":"Borehole image logs greatly facilitate detailed characterization of rock formations, especially for the highly heterogeneous and anisotropic carbonate rocks. However, interpreting image logs requires massive time and workforce and lacks consistency and repeatability because it relies heavily on a human interpreter's expertise, experience, and alertness. Thus, we propose to train an end-to-end deep neural network (DNN) for instant and consistent facies classification of carbonate rocks from acoustic image logs and gamma ray logs. The DNN is modified from the well-known U-Net for image segmentation. The training data are composed of two datasets: (1) manually labeled field data measured by different imaging tools from the geologically complex Brazilian pre-salt region and (2) noise-free synthetic data. Some short sections of the field data that are challenging for manual labeling due to entangled features and noises or low resolution are left unlabeled for a blind test after training. All labeled data are divided into a training set, a validation set, and a test set to avoid over-fitting. We demonstrate that the trained DNN achieves 77% classification accuracy for the test set and provides reasonable predictions for the challenging unlabeled sets. It is a great achievement given the complexity and variability of the field data. Compared with manual classification, our DNN provides more consistent and higher-resolution predictions in a highly efficient manner and thus dramatically contributes to automatic image log interpretation.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49461972","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}
The complex of depositional, burial, and diagenetic histories of the Late Cretaceous Nezzazat Group sandstones in Northeastern Africa present the main challenges with regard to reservoir quality. The quality of commercial reservoirs is maintained despite deep burial and the associated high temperature and pressure. The study presents optimum integration of different dataset to address the reservoir quality and reservoir performance controllers. The dataset includes measured porosity and permeability, petrographic point counting data, grain size analysis, X-ray diffraction data, scanning electron microscopy and compaction porosity loss by. The depositional controls on the reservoir quality are the facies, where the higher quality found in the channel and the upper shoreface settings. The coarse-grained sandstone associated with better reservoir quality. The large intergranular porosity is the main porosity control to the fluid to flow. The massive and laminated sandstones are the best quality facies. The labile grains (feldspars and mica) control the permeability distribution. While the secondary diagenetic controllers are the carbonate cementation that inhibited the effects of compaction. The siderite cementation has resulted in a micropore dominated and highly tortuous pore system. Total porosity has largely been preserved in the siderite-cemented sample but virtually eliminated in the dolomite cemented. Low volume of illite associated with better reservoir quality. While the better reservoir quality associated with abundant quartz cementation that protected the primary porosity from compaction. Compaction act as a significant porosity loss factor during diagenesis. Authigenic kaolinite does not significantly affect the reservoir quality. The reservoir sensitivity to formation damage come from the potential for fines (kaolinite, illitic clays, siderite and pyrite) migration within the pore system that are readily to mobilize by fluid flow.
{"title":"Depositional and Diagenetic Controllers on the Sandstone Reservoir Quality of the Late Cretaceous Sediments, Gulf of Suez Basin","authors":"A. Kassem","doi":"10.1190/int-2022-0093.1","DOIUrl":"https://doi.org/10.1190/int-2022-0093.1","url":null,"abstract":"The complex of depositional, burial, and diagenetic histories of the Late Cretaceous Nezzazat Group sandstones in Northeastern Africa present the main challenges with regard to reservoir quality. The quality of commercial reservoirs is maintained despite deep burial and the associated high temperature and pressure. The study presents optimum integration of different dataset to address the reservoir quality and reservoir performance controllers. The dataset includes measured porosity and permeability, petrographic point counting data, grain size analysis, X-ray diffraction data, scanning electron microscopy and compaction porosity loss by. The depositional controls on the reservoir quality are the facies, where the higher quality found in the channel and the upper shoreface settings. The coarse-grained sandstone associated with better reservoir quality. The large intergranular porosity is the main porosity control to the fluid to flow. The massive and laminated sandstones are the best quality facies. The labile grains (feldspars and mica) control the permeability distribution. While the secondary diagenetic controllers are the carbonate cementation that inhibited the effects of compaction. The siderite cementation has resulted in a micropore dominated and highly tortuous pore system. Total porosity has largely been preserved in the siderite-cemented sample but virtually eliminated in the dolomite cemented. Low volume of illite associated with better reservoir quality. While the better reservoir quality associated with abundant quartz cementation that protected the primary porosity from compaction. Compaction act as a significant porosity loss factor during diagenesis. Authigenic kaolinite does not significantly affect the reservoir quality. The reservoir sensitivity to formation damage come from the potential for fines (kaolinite, illitic clays, siderite and pyrite) migration within the pore system that are readily to mobilize by fluid flow.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45591686","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}
Nicolas Clausolles, P. Collon, M. Irakarama, G. Caumon
Variations in the migration velocity model directly affect the position of the imaged reflectors in the subsurface, leading to structural imaging uncertainties. These uncertainties are not explicitly addressed when trying to deterministically build an adequate velocity model. This paper presents a new stochastic geology-controlled velocity modeling method handling the possible presence of a salt weld. This permits to generate a large set of geological scenarios and associated velocity models. Each model is used to remigrate the seismic data. Then, a statistical analysis of the resulting seismic images is performed to quantify the local variability of the seismic responses. The approach is applied to the imaging of salt diapirs, in an iterative scheme (migrate, pick and update). The results show that, similarly to stacking common mid-point gathers, the statistical analysis preferentially preserves recurrent features from an image to another. In particular, this analysis permits to distinguish between connected and detached diapirs without prior knowledge about their connectivity, highlighting the potential of the method to resolve important aspects about basin and reservoir architecture. More generally, it provides quantitative information on the parts of the seismic image most sensitive to migration velocity variations, which opens interesting perspective to quantitative interpretation uncertainty assessment. Finally, the presented application also suggests that it is possible to significantly improve the quality of the generated seismic images by sampling many possible geological scenarios.
{"title":"Stochastic velocity modeling for assessment of imaging uncertainty during seismic migration: application to salt bodies","authors":"Nicolas Clausolles, P. Collon, M. Irakarama, G. Caumon","doi":"10.1190/int-2022-0071.1","DOIUrl":"https://doi.org/10.1190/int-2022-0071.1","url":null,"abstract":"Variations in the migration velocity model directly affect the position of the imaged reflectors in the subsurface, leading to structural imaging uncertainties. These uncertainties are not explicitly addressed when trying to deterministically build an adequate velocity model. This paper presents a new stochastic geology-controlled velocity modeling method handling the possible presence of a salt weld. This permits to generate a large set of geological scenarios and associated velocity models. Each model is used to remigrate the seismic data. Then, a statistical analysis of the resulting seismic images is performed to quantify the local variability of the seismic responses. The approach is applied to the imaging of salt diapirs, in an iterative scheme (migrate, pick and update). The results show that, similarly to stacking common mid-point gathers, the statistical analysis preferentially preserves recurrent features from an image to another. In particular, this analysis permits to distinguish between connected and detached diapirs without prior knowledge about their connectivity, highlighting the potential of the method to resolve important aspects about basin and reservoir architecture. More generally, it provides quantitative information on the parts of the seismic image most sensitive to migration velocity variations, which opens interesting perspective to quantitative interpretation uncertainty assessment. Finally, the presented application also suggests that it is possible to significantly improve the quality of the generated seismic images by sampling many possible geological scenarios.","PeriodicalId":51318,"journal":{"name":"Interpretation-A Journal of Subsurface Characterization","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42395674","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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