G. Hursán, Andre Silva, Marie Van Steene, A. Mutina
This paper presents recent results obtained from a new 4.75-in. logging-while-drilling (LWD) nuclear magnetic resonance (NMR) tool. Data from several wells provided real-time operational insight and new petrophysical learnings. The new LWD technology offers an innovative capability to simultaneously measure NMR T1 and T2 distributions with reduced sensitivity to drilling mud conductivity and a real-time sensor motion-warning system. The real-time T1 and T2 spectra compare favorably with the data set retrieved from the tool memory. The LWD NMR measurements were followed by wireline (WL) NMR logging for comparison in three wells. In carbonate reservoirs, the main objective was to evaluate the new NMR tool’s capability in resolving carbonate pore size with slow NMR relaxation rates. Another set of NMR logs contained time-lapse repeat passes in a well drilled with oil-based mud (OBM) that traversed a clastic reservoir. The sequence of measurements identified rock types and provided a unique insight into the mud filtrate invasion process. In a carbonate reservoir, the LWD NMR real-time partial porosity estimates were in excellent agreement with the core-calibrated WL micro-, meso-, and macropore volumes. Another carbonate formation contained high-permeability layers embedded in a microporous rock, where the real-time LWD NMR logs successfully located the high-quality rock zones, later verified by WL logging. In the clastic reservoir, the while-drilling LWD NMR data indicated native light hydrocarbons, whereas the subsequent LWD reaming and WL NMR passes showed a displacement of native hydrocarbons by oil-based mud filtrate (OBMF). The native hydrocarbon signature observed by the LWD NMR tool was in good agreement with the mud gas log. OBMF invasion occurred shortly after drilling, indicated by the differences observed in the LWD NMR relogged data acquired several hours after the while-drilling pass. The WL NMR data, logged about 4 days after drilling, showed advanced stages of OBMF invasion, including formation water displacement and wettability changes in intermediate and large pores. Finally, the environmental noise remained low in the LWD NMR data set acquired in a well in which the mud salinity changed by several folds, indicating that mud salinity had little effect on the quality of LWD NMR logs in slim holes. The new slimhole LWD NMR technology demonstrated its robust capability to provide T1 and T2 logs through several examples. For the first time, a time-lapse comparison of NMR logs showed that OBMF invasion could occur in silty sands with high capillary-bound fluid fractions.
{"title":"Learnings From a New Slimhole LWD NMR Technology","authors":"G. Hursán, Andre Silva, Marie Van Steene, A. Mutina","doi":"10.30632/pjv63n3-2022a7","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a7","url":null,"abstract":"This paper presents recent results obtained from a new 4.75-in. logging-while-drilling (LWD) nuclear magnetic resonance (NMR) tool. Data from several wells provided real-time operational insight and new petrophysical learnings. The new LWD technology offers an innovative capability to simultaneously measure NMR T1 and T2 distributions with reduced sensitivity to drilling mud conductivity and a real-time sensor motion-warning system. The real-time T1 and T2 spectra compare favorably with the data set retrieved from the tool memory. The LWD NMR measurements were followed by wireline (WL) NMR logging for comparison in three wells. In carbonate reservoirs, the main objective was to evaluate the new NMR tool’s capability in resolving carbonate pore size with slow NMR relaxation rates. Another set of NMR logs contained time-lapse repeat passes in a well drilled with oil-based mud (OBM) that traversed a clastic reservoir. The sequence of measurements identified rock types and provided a unique insight into the mud filtrate invasion process. In a carbonate reservoir, the LWD NMR real-time partial porosity estimates were in excellent agreement with the core-calibrated WL micro-, meso-, and macropore volumes. Another carbonate formation contained high-permeability layers embedded in a microporous rock, where the real-time LWD NMR logs successfully located the high-quality rock zones, later verified by WL logging. In the clastic reservoir, the while-drilling LWD NMR data indicated native light hydrocarbons, whereas the subsequent LWD reaming and WL NMR passes showed a displacement of native hydrocarbons by oil-based mud filtrate (OBMF). The native hydrocarbon signature observed by the LWD NMR tool was in good agreement with the mud gas log. OBMF invasion occurred shortly after drilling, indicated by the differences observed in the LWD NMR relogged data acquired several hours after the while-drilling pass. The WL NMR data, logged about 4 days after drilling, showed advanced stages of OBMF invasion, including formation water displacement and wettability changes in intermediate and large pores. Finally, the environmental noise remained low in the LWD NMR data set acquired in a well in which the mud salinity changed by several folds, indicating that mud salinity had little effect on the quality of LWD NMR logs in slim holes. The new slimhole LWD NMR technology demonstrated its robust capability to provide T1 and T2 logs through several examples. For the first time, a time-lapse comparison of NMR logs showed that OBMF invasion could occur in silty sands with high capillary-bound fluid fractions.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126244972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An overview of NMR data processing is provided with more emphasis on the algorithms and interpretation methods commonly used in everyday NMR logging practices. For many of these algorithms and methods discussed in this paper, either enough technical details or field examples are given for better understanding NMR data processing and interpretation, but more focus is given to the algorithms’ applicable scope and the related issues encountered in the practice of NMR logging interpretation. The latest developments in NMR data processing and interpretation are also discussed.
{"title":"NMR Logging Data Processing","authors":"Wei Shao, R. Balliet","doi":"10.30632/pjv63n3-2022a3","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a3","url":null,"abstract":"An overview of NMR data processing is provided with more emphasis on the algorithms and interpretation methods commonly used in everyday NMR logging practices. For many of these algorithms and methods discussed in this paper, either enough technical details or field examples are given for better understanding NMR data processing and interpretation, but more focus is given to the algorithms’ applicable scope and the related issues encountered in the practice of NMR logging interpretation. The latest developments in NMR data processing and interpretation are also discussed.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130116695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Standardized and benchmarked wettability characterization and quantification workflows are lacking in unconventional reservoir development. Quantification of in-situ wettability and changes due to wettability alteration efforts can assist with completions decisions, and economic oil production. This manuscript summarizes the establishment and validation of an NMR wettability index (NWI) for unconventional rocks. The method builds upon Looyestijn’s NMR wettability analysis methods for conventional rocks and has been tested on core plug samples from a variety of major producing unconventional reservoirs. It will be of interest to readers to note the marked range of wettability values quantified among the aforementioned tight formations. Our NWI model is well suited for data sets featuring complex oil and water T2 spectra with multiple peaks, common features of unconventional rock spectra. The results were subjected to comprehensive experimental and analytical validation, including complementary 3D NMR imaging and replication of the experiments with D2O. The validation procedure and advantages of the approach over other NMR wettability models are discussed in this review. Finally, best practices are detailed so that the SCAL methodology can be deployed on a larger scale.
{"title":"NMR-Based Wettability Index for Unconventional Rocks","authors":"M. Dick, D. Veselinović, R. Bonnie, Shaina Kelly","doi":"10.30632/pjv63n3-2022a9","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a9","url":null,"abstract":"Standardized and benchmarked wettability characterization and quantification workflows are lacking in unconventional reservoir development. Quantification of in-situ wettability and changes due to wettability alteration efforts can assist with completions decisions, and economic oil production. This manuscript summarizes the establishment and validation of an NMR wettability index (NWI) for unconventional rocks. The method builds upon Looyestijn’s NMR wettability analysis methods for conventional rocks and has been tested on core plug samples from a variety of major producing unconventional reservoirs. It will be of interest to readers to note the marked range of wettability values quantified among the aforementioned tight formations. Our NWI model is well suited for data sets featuring complex oil and water T2 spectra with multiple peaks, common features of unconventional rock spectra. The results were subjected to comprehensive experimental and analytical validation, including complementary 3D NMR imaging and replication of the experiments with D2O. The validation procedure and advantages of the approach over other NMR wettability models are discussed in this review. Finally, best practices are detailed so that the SCAL methodology can be deployed on a larger scale.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116809528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Thern, A. Kotwicki, N. Ritzmann, J. Petersen, O. Mohnke
The presence of gas in hydrocarbon reservoirs has a distinct effect on commonly used porosity logging measurements such as density, neutron, and nuclear magnetic resonance (NMR). Although the effect of gas on NMR measurements is well understood, it remains difficult to estimate true formation porosity and hydrocarbon (HC) saturation exclusively from NMR data in gas-bearing formations. The hydrogen index (HI) of gas is much smaller than one and causes an underestimation of the measured NMR porosity. Unless temperature, pressure, HC composition, and saturation in the volume sensed by NMR are known accurately, compensating for the effect of gas is not easily accomplished. This paper compares different approaches for NMR gas zone analysis, and it introduces a new method integrating NMR logging data with a HI curve derived from mud gas surface logging. The results are connected to a full and consistent petrophysical reservoir description. Data and results from two wells drilled in a North Sea clastic reservoir are presented. The reservoir is dominated by thick units of sandstone, deposited in a submarine turbidite fan, with high porosity and high permeability. The wells were logged with triple-combo (i.e., gamma ray, density, neutron, and resistivity), NMR, and formation tester (FT) tools while drilling across gas, oil, and water intervals. Basic mud gas data are available from surface logging. Uncorrected NMR porosity shows an average porosity underestimation of 6 p.u. in the gas zone compared to triple-combo computer-processed interpretation (CPI) processing. The standalone evaluation of NMR data by a T2 cutoff approach and dual wait-time (DTW) data processing reduces the average porosity mismatch but results in zones of under- and overcorrection of the gas effect. Combining NMR DTW data with density improves the results and reduces the average porosity mismatch to less than 2 p.u. Compositional information from the mud gas data validates an inferred trend of fluid property variation in gas and oil zones across the reservoir and is used to derive a continuous HI log for further improving porosity and gas saturation estimation. Complementary to the results of the integrated data evaluation, we show independent results from mud gas data evaluation using a recently implemented method that provides independent porosity, permeability, and saturation indexes. Adverse conditions for the different approaches, including invasion, variations in mineralogy, and the limited vertical resolution of mud gas data, are discussed. Finally, the benefits and potential of combining NMR, mud gas, and triple-combo data are summarized.
{"title":"Formation Evaluation Using NMR, Mud Gas, and Triple-Combo Data – A Norwegian Logging-While-Drilling Case History","authors":"H. Thern, A. Kotwicki, N. Ritzmann, J. Petersen, O. Mohnke","doi":"10.30632/pjv63n3-2022a6","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a6","url":null,"abstract":"The presence of gas in hydrocarbon reservoirs has a distinct effect on commonly used porosity logging measurements such as density, neutron, and nuclear magnetic resonance (NMR). Although the effect of gas on NMR measurements is well understood, it remains difficult to estimate true formation porosity and hydrocarbon (HC) saturation exclusively from NMR data in gas-bearing formations. The hydrogen index (HI) of gas is much smaller than one and causes an underestimation of the measured NMR porosity. Unless temperature, pressure, HC composition, and saturation in the volume sensed by NMR are known accurately, compensating for the effect of gas is not easily accomplished. This paper compares different approaches for NMR gas zone analysis, and it introduces a new method integrating NMR logging data with a HI curve derived from mud gas surface logging. The results are connected to a full and consistent petrophysical reservoir description. Data and results from two wells drilled in a North Sea clastic reservoir are presented. The reservoir is dominated by thick units of sandstone, deposited in a submarine turbidite fan, with high porosity and high permeability. The wells were logged with triple-combo (i.e., gamma ray, density, neutron, and resistivity), NMR, and formation tester (FT) tools while drilling across gas, oil, and water intervals. Basic mud gas data are available from surface logging. Uncorrected NMR porosity shows an average porosity underestimation of 6 p.u. in the gas zone compared to triple-combo computer-processed interpretation (CPI) processing. The standalone evaluation of NMR data by a T2 cutoff approach and dual wait-time (DTW) data processing reduces the average porosity mismatch but results in zones of under- and overcorrection of the gas effect. Combining NMR DTW data with density improves the results and reduces the average porosity mismatch to less than 2 p.u. Compositional information from the mud gas data validates an inferred trend of fluid property variation in gas and oil zones across the reservoir and is used to derive a continuous HI log for further improving porosity and gas saturation estimation. Complementary to the results of the integrated data evaluation, we show independent results from mud gas data evaluation using a recently implemented method that provides independent porosity, permeability, and saturation indexes. Adverse conditions for the different approaches, including invasion, variations in mineralogy, and the limited vertical resolution of mud gas data, are discussed. Finally, the benefits and potential of combining NMR, mud gas, and triple-combo data are summarized.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116923399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Olabode Ijasan, J. Macquaker, Mathilde Luycx, Shehab Alzobaidi, Emmanuel O. Oyewole, Mark D. Rudnicki
The rock-pore textural properties in unconventional fine-grained reservoirs are much more complicated than in conventional reservoirs. In fine-grained rocks, this complexity derives from very small component grain assemblages (clay and silt fractions) and very small pores (nano- to microsizes) overprinted by diagenesis. It is further compounded by the pores being developed in intergranular, grain dissolution, and organic-associated-intragranular voids. Additionally, because locally sourced hydrocarbons in unconventional reservoirs, in contrast to migrated hydrocarbons that are present in conventional reservoirs, exist within similar pore sizes as the original saturating water phase, they create geometrically complex fluid distributions. These imply that, in the context of nuclear magnetic resonance (NMR) logging and petrophysical interpretation of tight oil unconventional reservoirs, pore size can no longer be considered a proxy for fluid type and vice versa. This means using T2 or T1 cutoffs may give inaccurate predictions. Current industry applications of NMR T1-T2 logging have demonstrated reliable interpretation of fluid types and water saturation. However, because petrophysical controls of advanced relaxation effects (such as surface and bulk fluid relaxation properties, pore-size distribution, and wettability) are not properly understood, these applications have been limited to estimating fluid saturations and have not been applied to estimating pore sizes. We extend the application of NMR T1-T2 measurements in tight oil unconventional reservoirs to model pore-size distributions by using apparent surface relaxivities and bulk relaxation times that have been jointly estimated from poro-fluid relaxations. To test these predictions, modeled pore-size distributions are compared to rock-pore textural properties from petrographic images of core samples. Such comparison allows us to derive insights into controls of mudstone reservoir quality (RQ) in conjunction with the impact of rock fabric endmembers (e.g., matrix-supported clays, grain-supported framework, diagenetic cements, and solid organic matter) on pore-size distributions. With these assumptions in mind, it follows, based on the Kozeny-Carman formulation, that unconventional rock permeability is reliably predicted from the NMR-based pore-size distributions. Furthermore, we deduce the impact of mineral assemblages in the Herron permeability model to infer influence on rock textural properties and ultimately predict permeability in limited data environments. This paper introduces a novel approach to estimate pore-size distributions per fluid type (water and hydrocarbons) from NMR T1-T2 measurements in unconventional reservoirs. Additionally, petrophysical controls of RQ, storage, and transport properties are derived from NMR-based pore-size distributions and mineral assemblages. This enables more reliable RQ and permeability assessment than typical T2- or T1-cutoff methods.
{"title":"NMR T1-T2 Logging in Unconventional Reservoirs: Pore-Size Distribution, Permeability, and Reservoir Quality","authors":"Olabode Ijasan, J. Macquaker, Mathilde Luycx, Shehab Alzobaidi, Emmanuel O. Oyewole, Mark D. Rudnicki","doi":"10.30632/pjv63n3-2022a5","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a5","url":null,"abstract":"The rock-pore textural properties in unconventional fine-grained reservoirs are much more complicated than in conventional reservoirs. In fine-grained rocks, this complexity derives from very small component grain assemblages (clay and silt fractions) and very small pores (nano- to microsizes) overprinted by diagenesis. It is further compounded by the pores being developed in intergranular, grain dissolution, and organic-associated-intragranular voids. Additionally, because locally sourced hydrocarbons in unconventional reservoirs, in contrast to migrated hydrocarbons that are present in conventional reservoirs, exist within similar pore sizes as the original saturating water phase, they create geometrically complex fluid distributions. These imply that, in the context of nuclear magnetic resonance (NMR) logging and petrophysical interpretation of tight oil unconventional reservoirs, pore size can no longer be considered a proxy for fluid type and vice versa. This means using T2 or T1 cutoffs may give inaccurate predictions. Current industry applications of NMR T1-T2 logging have demonstrated reliable interpretation of fluid types and water saturation. However, because petrophysical controls of advanced relaxation effects (such as surface and bulk fluid relaxation properties, pore-size distribution, and wettability) are not properly understood, these applications have been limited to estimating fluid saturations and have not been applied to estimating pore sizes. We extend the application of NMR T1-T2 measurements in tight oil unconventional reservoirs to model pore-size distributions by using apparent surface relaxivities and bulk relaxation times that have been jointly estimated from poro-fluid relaxations. To test these predictions, modeled pore-size distributions are compared to rock-pore textural properties from petrographic images of core samples. Such comparison allows us to derive insights into controls of mudstone reservoir quality (RQ) in conjunction with the impact of rock fabric endmembers (e.g., matrix-supported clays, grain-supported framework, diagenetic cements, and solid organic matter) on pore-size distributions. With these assumptions in mind, it follows, based on the Kozeny-Carman formulation, that unconventional rock permeability is reliably predicted from the NMR-based pore-size distributions. Furthermore, we deduce the impact of mineral assemblages in the Herron permeability model to infer influence on rock textural properties and ultimately predict permeability in limited data environments. This paper introduces a novel approach to estimate pore-size distributions per fluid type (water and hydrocarbons) from NMR T1-T2 measurements in unconventional reservoirs. Additionally, petrophysical controls of RQ, storage, and transport properties are derived from NMR-based pore-size distributions and mineral assemblages. This enables more reliable RQ and permeability assessment than typical T2- or T1-cutoff methods.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121028837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes the application of machine-learning techniques for unlocking the full potential of nuclear magnetic resonance (NMR), using a case study from the Seven Heads gas field. This field has long been recognized but was not developed due to a variety of technical challenges, including the thin-bedded nature of the sediments and the presence of both mobile and immobile viscous residual oil. The oil is a highly viscous liquid which, if produced, could block production tubing due to the shallow depth of the reservoir and associated low pressures. To produce dry gas successfully, identification of both oil and gas zones was necessary to enable gas zones to be perforated and oil zones to be excluded. During the development drilling campaign, the reservoir was appraised using a formation evaluation program specifically designed to address the presence of oil within the thinly bedded reservoir. In conjunction with core data and high-resolution electric logs, NMR logs were used to identify and avoid perforating zones with higher oil saturations. Formation fluid types were derived from the NMR using a pattern recognition technique that analyzes the entire shape of the T1 and T2 distributions to derive the volumes of gas, oil, and water. This machine-learning technique was calibrated using Dean and Stark fluid analysis data and enabled the prediction of continuous water, gas, and oil saturation curves. The results were used to ensure that the perforation strategy avoided oil-bearing sands. This paper describes how the NMR, together with machine learning, has enabled a complex tight gas field to be developed.
{"title":"Unlocking the Full Potential of NMR Using Machine Learning: A Case Study of a Gas Field With an Oil Problem","authors":"S. Cuddy","doi":"10.30632/pjv63n3-2022a2","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a2","url":null,"abstract":"This paper describes the application of machine-learning techniques for unlocking the full potential of nuclear magnetic resonance (NMR), using a case study from the Seven Heads gas field. This field has long been recognized but was not developed due to a variety of technical challenges, including the thin-bedded nature of the sediments and the presence of both mobile and immobile viscous residual oil. The oil is a highly viscous liquid which, if produced, could block production tubing due to the shallow depth of the reservoir and associated low pressures. To produce dry gas successfully, identification of both oil and gas zones was necessary to enable gas zones to be perforated and oil zones to be excluded. During the development drilling campaign, the reservoir was appraised using a formation evaluation program specifically designed to address the presence of oil within the thinly bedded reservoir. In conjunction with core data and high-resolution electric logs, NMR logs were used to identify and avoid perforating zones with higher oil saturations. Formation fluid types were derived from the NMR using a pattern recognition technique that analyzes the entire shape of the T1 and T2 distributions to derive the volumes of gas, oil, and water. This machine-learning technique was calibrated using Dean and Stark fluid analysis data and enabled the prediction of continuous water, gas, and oil saturation curves. The results were used to ensure that the perforation strategy avoided oil-bearing sands. This paper describes how the NMR, together with machine learning, has enabled a complex tight gas field to be developed.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126338128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pedro Romero Rojas, L. Tagarieva, A. Panchal, Shaikha AlTurki, A. Qubian
The effect of mud filtrate and eventually fine migrations in high-quality rocks considerably influence the reading of NMR and conventional logs. It poses a challenge in extracting useful information that can contribute to the petrophysical evaluation of the virgin zone, e.g., the rock quality index. This is critical for determining the permeability index and the saturation exponent n required for accurate determination of the water saturation. The rock quality index is understood as the ratio between free-fluid volume (FFV) and bound-fluid volume (BFV). This is equivalent to the pore-throat radius, which dominates fluid flow, that is negatively affected by the fine migration. This is reflected in a reduction of the porosity filled by free fluid. The free-fluid porosity undercall is corrected with the help of deeper-reading density data. After this correction, the NMR-derived permeability in the flushed zone, probably damaged by migrated fines, is used to calculate the permeability in the virgin zone. The determination of the oil saturation in the flushed zone from NMR logs was done in two ways—first, by applying statistically based machine-learning tools, and secondly, by applying the widely used 2D-NMR method, diffusion vs. T2 maps. Comparative analysis of these two methods shows that both lead to consistent results. The water saturation in the flushed zone is estimated to be eight times higher than in the virgin zone because of the high degree of invasion.
{"title":"NMR-Supported Near-Wellbore Data Analysis to Improve the Petrophysical Evaluation of a Sandstone Reservoir Drilled With Barite-Enriched Water-Based Mud","authors":"Pedro Romero Rojas, L. Tagarieva, A. Panchal, Shaikha AlTurki, A. Qubian","doi":"10.30632/pjv63n3-2022a4","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a4","url":null,"abstract":"The effect of mud filtrate and eventually fine migrations in high-quality rocks considerably influence the reading of NMR and conventional logs. It poses a challenge in extracting useful information that can contribute to the petrophysical evaluation of the virgin zone, e.g., the rock quality index. This is critical for determining the permeability index and the saturation exponent n required for accurate determination of the water saturation. The rock quality index is understood as the ratio between free-fluid volume (FFV) and bound-fluid volume (BFV). This is equivalent to the pore-throat radius, which dominates fluid flow, that is negatively affected by the fine migration. This is reflected in a reduction of the porosity filled by free fluid. The free-fluid porosity undercall is corrected with the help of deeper-reading density data. After this correction, the NMR-derived permeability in the flushed zone, probably damaged by migrated fines, is used to calculate the permeability in the virgin zone. The determination of the oil saturation in the flushed zone from NMR logs was done in two ways—first, by applying statistically based machine-learning tools, and secondly, by applying the widely used 2D-NMR method, diffusion vs. T2 maps. Comparative analysis of these two methods shows that both lead to consistent results. The water saturation in the flushed zone is estimated to be eight times higher than in the virgin zone because of the high degree of invasion.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130524679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.30632/pjv63n3-2022a10
Edmilson Helton Rios, R. B. de Vasconcellos Azeredo, A. Moss, T. Pritchard, Ana Beatriz Guedes Domingues
The estimation of continuous downhole permeability is widely performed by nuclear magnetic resonance (NMR) using the classical Seevers-Kenyon and Timur-Coates models. The first approach uses an average of the relaxation times, whereas the latter approach is based on the fractional fluid content computed from a relaxation time distribution cutoff. However, several case studies in the literature reported that these models might fail, especially when applied to complex carbonate rocks in which permeability is often less correlated to porosity, irreducible water saturation, and relaxation times. This study develops and evaluates perm-estimators that use multiple relaxation times, proving that they are a general case of the classical models. The so-called multivariate estimators are calibrated with core permeability using principal component regression, which describes NMR variables in a simple and linear-independent space according to data variance. An important feature of the multivariate approach is the possibility of simultaneously using longitudinal T1 and transverse T2 relaxation times or simply using a specific segment of their distribution. Moreover, the multivariate estimators can also be applied to size-scaled T1,2 distributions for cases in which relaxation times are less sensitive to permeability, such as the carbonate rocks studied in this work. By employing mercury injection capillary pressure (MICP) data for the NMR size scaling, permeability estimates are improved considerably compared to the nonscaled estimates. The superior results achieved with the novel multivariate estimators over the classical models indicate that core and NMR well-logging data should be better explored to improve the accuracy of permeability estimates.
{"title":"Estimating the Permeability of Rocks by Principal Component Regressions of NMR and MICP Data","authors":"Edmilson Helton Rios, R. B. de Vasconcellos Azeredo, A. Moss, T. Pritchard, Ana Beatriz Guedes Domingues","doi":"10.30632/pjv63n3-2022a10","DOIUrl":"https://doi.org/10.30632/pjv63n3-2022a10","url":null,"abstract":"The estimation of continuous downhole permeability is widely performed by nuclear magnetic resonance (NMR) using the classical Seevers-Kenyon and Timur-Coates models. The first approach uses an average of the relaxation times, whereas the latter approach is based on the fractional fluid content computed from a relaxation time distribution cutoff. However, several case studies in the literature reported that these models might fail, especially when applied to complex carbonate rocks in which permeability is often less correlated to porosity, irreducible water saturation, and relaxation times. This study develops and evaluates perm-estimators that use multiple relaxation times, proving that they are a general case of the classical models. The so-called multivariate estimators are calibrated with core permeability using principal component regression, which describes NMR variables in a simple and linear-independent space according to data variance. An important feature of the multivariate approach is the possibility of simultaneously using longitudinal T1 and transverse T2 relaxation times or simply using a specific segment of their distribution. Moreover, the multivariate estimators can also be applied to size-scaled T1,2 distributions for cases in which relaxation times are less sensitive to permeability, such as the carbonate rocks studied in this work. By employing mercury injection capillary pressure (MICP) data for the NMR size scaling, permeability estimates are improved considerably compared to the nonscaled estimates. The superior results achieved with the novel multivariate estimators over the classical models indicate that core and NMR well-logging data should be better explored to improve the accuracy of permeability estimates.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115256511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Casing deformation and tubing eccentricity is a concern in the oil and gas industry for safety and operational reasons. Casing deformation or tubing eccentricity originates from various sources such as well completion, corrosion, formation swelling, collapse, and salt dome creep. It is important to implement a well-integrity surveillance program covering all casing and tubing strings for the full well life cycle from initial completion to abandonment. However, there has been no effective through-tubing logging method to evaluate the casing string for deformation and eccentricity. This paper describes a new Deformation-and-Eccentricity (DEC) tool that is based on electromagnetic technology and designed to measure casing deformation and tubing eccentricity while logging inside completion tubing. The DEC tool generates a unique compressed-and-focused magnetic field that provides an increased signal-to-noise ratio (SNR). The tool then employs an array of magnetic sensors to measure the magnetic flux density distributions azimuthally around the tool. The tool’s compressed-and-focused magnetic field is designed to (1) saturate the magnetic flux of the tubing, (2) to inject more magnetic flux into the first casing behind the tubing, and (3) to increase the signal measurement sensitivity and SNR. The sensor matrix measures flux density changes that correspond to variations in distance between tubing and casing. The high-resolution azimuthal magnetic sensor matrix delivers high-accuracy measurements that are used to image the flux density changes. A finite-element-based forward modeling and an optimized Gaussian processes regression method have been developed to process the raw logging data. The DEC tool has a built-in orientation measurement capability that is based on gyroscopes and accelerometers that are used to align the deformation and eccentricity images and index curves as well as the tubing thickness image. The tool specifications state accuracies of 1% of the eccentricity ratio and 5% of the deformation ratio in the range of casing OD up to 13.375 in. DEC technology provides an advanced answer product for through-tubing casing deformation and eccentricity measurements in downhole well-integrity and plug-abandonment applications. When combined with other well-integrity measurements such as a multifinger caliper and multipipe thickness log tool, a complete well-integrity evaluation can be achieved throughout the life cycle of a well. For example, significant casing deformation can often indicate possible damaged cement behind the casing. Other applications for the technology include locating tubing clamps for fiber-optic cables and control lines and determining the orientation of multistring tubing completions. Performances of the tool have been validated through research simulations, lab tests, and field trials. This paper includes a field case study of a deviated gas production well with tubing buckling and casing micro dogleg.
{"title":"Through-Tubing Casing Deformation and Tubing Eccentricity Image Tool for Well-Integrity Monitoring and Plug Abandonment","authors":"Qinshan Yang, Kuang Qin, J. Olson, M. Rourke","doi":"10.30632/pjv63n2-2022a1","DOIUrl":"https://doi.org/10.30632/pjv63n2-2022a1","url":null,"abstract":"Casing deformation and tubing eccentricity is a concern in the oil and gas industry for safety and operational reasons. Casing deformation or tubing eccentricity originates from various sources such as well completion, corrosion, formation swelling, collapse, and salt dome creep. It is important to implement a well-integrity surveillance program covering all casing and tubing strings for the full well life cycle from initial completion to abandonment. However, there has been no effective through-tubing logging method to evaluate the casing string for deformation and eccentricity. This paper describes a new Deformation-and-Eccentricity (DEC) tool that is based on electromagnetic technology and designed to measure casing deformation and tubing eccentricity while logging inside completion tubing. The DEC tool generates a unique compressed-and-focused magnetic field that provides an increased signal-to-noise ratio (SNR). The tool then employs an array of magnetic sensors to measure the magnetic flux density distributions azimuthally around the tool. The tool’s compressed-and-focused magnetic field is designed to (1) saturate the magnetic flux of the tubing, (2) to inject more magnetic flux into the first casing behind the tubing, and (3) to increase the signal measurement sensitivity and SNR. The sensor matrix measures flux density changes that correspond to variations in distance between tubing and casing. The high-resolution azimuthal magnetic sensor matrix delivers high-accuracy measurements that are used to image the flux density changes. A finite-element-based forward modeling and an optimized Gaussian processes regression method have been developed to process the raw logging data. The DEC tool has a built-in orientation measurement capability that is based on gyroscopes and accelerometers that are used to align the deformation and eccentricity images and index curves as well as the tubing thickness image. The tool specifications state accuracies of 1% of the eccentricity ratio and 5% of the deformation ratio in the range of casing OD up to 13.375 in. DEC technology provides an advanced answer product for through-tubing casing deformation and eccentricity measurements in downhole well-integrity and plug-abandonment applications. When combined with other well-integrity measurements such as a multifinger caliper and multipipe thickness log tool, a complete well-integrity evaluation can be achieved throughout the life cycle of a well. For example, significant casing deformation can often indicate possible damaged cement behind the casing. Other applications for the technology include locating tubing clamps for fiber-optic cables and control lines and determining the orientation of multistring tubing completions. Performances of the tool have been validated through research simulations, lab tests, and field trials. This paper includes a field case study of a deviated gas production well with tubing buckling and casing micro dogleg.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130291980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Einar Madsen Storebø, M. L. Hjuler, Leonardo Teixeira Pinto Meireles, I. Fabricius
In hydrocarbon reservoirs, log analysis and core measurements provide the fundament for water and hydrocarbon saturation evaluation. In mixed mineral formations containing clay and metallic minerals, the electrical resistivity logging tools used for water saturation calculations are significantly affected due to the conductive nature of these minerals, which could result in an inaccurate saturation profile. In this study, we extend Archie’s equation for water saturation calculation in the Lower Cretaceous marly chalk formations in the Danish North Sea. Using Hashin-Shtrikman bounds, we investigate the phase mixing in the formation, providing a consistent and practical method for saturation evaluation in a mixed mineral heterogeneous formation containing conductive minerals.
{"title":"Effect of Pyrite in Water Saturation Evaluation of Clay-Rich Carbonate","authors":"Einar Madsen Storebø, M. L. Hjuler, Leonardo Teixeira Pinto Meireles, I. Fabricius","doi":"10.30632/pjv63n2-2022a3","DOIUrl":"https://doi.org/10.30632/pjv63n2-2022a3","url":null,"abstract":"In hydrocarbon reservoirs, log analysis and core measurements provide the fundament for water and hydrocarbon saturation evaluation. In mixed mineral formations containing clay and metallic minerals, the electrical resistivity logging tools used for water saturation calculations are significantly affected due to the conductive nature of these minerals, which could result in an inaccurate saturation profile. In this study, we extend Archie’s equation for water saturation calculation in the Lower Cretaceous marly chalk formations in the Danish North Sea. Using Hashin-Shtrikman bounds, we investigate the phase mixing in the formation, providing a consistent and practical method for saturation evaluation in a mixed mineral heterogeneous formation containing conductive minerals.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129075201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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