An underground stress state might be disturbed in an area, particularly adjusting to an active shear zone. Borehole breakouts (BOs) that appeared in a circular hole excavated in an inhomogeneous stress field might be tracked to identify the active shear zone. The present study aims to develop the breakout morphology analysis (BMA) algorithm to exploit the valuable attributes of borehole BOs including azimuth, width, and intensity (depth of elongation) of failure from wellbore ultrasonic imaging tools. In the current study, the extracted azimuthal information was surveyed to detect the active shear zone along the well. Ultrasonic data from five wells drilled in the doubly plunging Ahvaz Anticline located in Iran were collected for the purpose of algorithm verification. The multiwell correlation of the BOs’ azimuth generated by the algorithm in the Ahvaz Anticline suggests a shear plan dipping southwest-northeast direction is possibly active in the deep vertical wells. Similarly, the seismic reflection profile of the Ahvaz Anticline shows a track of detachment faulting system in the mid-Cretaceous sediments. The finding confirms that the raw ultrasonic traveling time is more applicable than other borehole image data, such as static and dynamic images of ultrasonic amplitude, in BO characterization.
{"title":"Active Fault Detection by an Automatic Breakout Geometry Characterization Algorithm from Ultrasonic Borehole Imager","authors":"Hamid Heydari Gholanlo, M. Nikkhah","doi":"10.2118/214673-pa","DOIUrl":"https://doi.org/10.2118/214673-pa","url":null,"abstract":"\u0000 An underground stress state might be disturbed in an area, particularly adjusting to an active shear zone. Borehole breakouts (BOs) that appeared in a circular hole excavated in an inhomogeneous stress field might be tracked to identify the active shear zone. The present study aims to develop the breakout morphology analysis (BMA) algorithm to exploit the valuable attributes of borehole BOs including azimuth, width, and intensity (depth of elongation) of failure from wellbore ultrasonic imaging tools. In the current study, the extracted azimuthal information was surveyed to detect the active shear zone along the well. Ultrasonic data from five wells drilled in the doubly plunging Ahvaz Anticline located in Iran were collected for the purpose of algorithm verification. The multiwell correlation of the BOs’ azimuth generated by the algorithm in the Ahvaz Anticline suggests a shear plan dipping southwest-northeast direction is possibly active in the deep vertical wells. Similarly, the seismic reflection profile of the Ahvaz Anticline shows a track of detachment faulting system in the mid-Cretaceous sediments. The finding confirms that the raw ultrasonic traveling time is more applicable than other borehole image data, such as static and dynamic images of ultrasonic amplitude, in BO characterization.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90954568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The complex fracture network from hydraulic fracturing can significantly improve oilwell productivity, so it is widely used in the field of unconventional reservoir development. However, accurate evaluation of the fracture spatial distribution remains a challenge. As a result, how to combine a variety of data to avoid data islands and identify and predict the space of fracture zone is of great importance. In this paper, we present a method and workflow based on the microseismic (MS) data combined with shear wave velocity data to estimate the physical parameters of subsurface media and improve the description and prediction accuracy for hydraulic fractures. The method analyzes MS events to construct the fracture spatial distribution and uses acoustic logging measurements to correct the magnitude of MS events and enhance the resolution. The corrected MS magnitude is mapped to the MS event space for Kriging interpolation analysis to predict the improved spatial distribution of fractures, which is available in the format of a 3D cloud image.
{"title":"Improving Prediction of Fracture Distribution Using Microseismic Data and Acoustic Logging Measurements","authors":"Yilin Liu, Guozhong Gao","doi":"10.2118/214677-pa","DOIUrl":"https://doi.org/10.2118/214677-pa","url":null,"abstract":"\u0000 The complex fracture network from hydraulic fracturing can significantly improve oilwell productivity, so it is widely used in the field of unconventional reservoir development. However, accurate evaluation of the fracture spatial distribution remains a challenge. As a result, how to combine a variety of data to avoid data islands and identify and predict the space of fracture zone is of great importance. In this paper, we present a method and workflow based on the microseismic (MS) data combined with shear wave velocity data to estimate the physical parameters of subsurface media and improve the description and prediction accuracy for hydraulic fractures. The method analyzes MS events to construct the fracture spatial distribution and uses acoustic logging measurements to correct the magnitude of MS events and enhance the resolution. The corrected MS magnitude is mapped to the MS event space for Kriging interpolation analysis to predict the improved spatial distribution of fractures, which is available in the format of a 3D cloud image.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"53 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82699589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a systematical review of the largest polymer flood project in the world, applied to multilayered, heterogeneous sandstone reservoirs in the giant Daqing Oilfield in China. First, reservoir and fluid characteristics are highlighted to understand the heterogeneity of the reservoir. Next, the project history is summarized, including laboratory studies, pilot tests, commercial tests, and fieldwide applications. Third, typical polymer flood performance and reservoir management measures are presented. Finally, key understandings and lessons learned from more than 50 years of experience are summarized. The La-Sa-Xing Field in the Daqing Field Complex contains three types of reservoir sands: Type I sand with high permeability, Type II sand with medium permeability, and Type III sand with low permeability. Polymer flood was studied in the laboratory in the mid 1960s, followed by small-scale pilots beginning in 1972 and industrial-scale pilots starting in 1993, all of which successfully reduced water cut and enhanced oil recovery. Fieldwide application commenced in 1996, targeting the Type I sand. With Type II sand being brought onstream in 2003, the project achieved a peak production of 253,000 BOPD in 2013. Polymer flood reduced water cut by 24.8%. Reservoir management measures, such as zonal injection, profile modification, hydraulic fracturing in low-permeability sand, and injection optimization, proved to be effective. Based on the water-cut performance, production can be divided into four stages: (1) water-cut decline, (2) low water cut, (3) rebound, and (4) water chase. Fit-for-purpose improved-oil-recovery measures were implemented for each stage to improve production performance. Key understandings and lessons learned include the following: (1) Polymer flood improves both sweeping and displacing efficiencies; (2) high interlayer permeability contrast leads to low incremental recovery; (3) variable well spacing should be adopted for different reservoir types; (4) adoption of large molecular weight (MW) and large slug size greatly enhances recovery; and (5) salt-resistant polymer is beneficial for produced water reinjection in Type II sand; (6) zonal injection increased swept reservoir zones by 9.8% and swept pay thickness by 10.3%; (7) profile modifications helped improve vertical conformance in injection wells and led to enhanced sweeping efficiency and extended low water-cut stage; and (8) optimization-recommended well spacing for Type I, Type II, and Type III sands is 10–15.5, 5.6–7.6, and 2.5–3.6 acres, respectively. In comparison with generally 6–8% incremental recovery by polymer flood in the industry, this project achieved an impressive incremental recovery of 12%, enhancing the oil recovery factor from 40% by primary recovery and waterflood to 52% stock tank oil initially in place (STOIIP). The progressive approach from laboratory experiments through pilots and finally to field application is a best practice for app
{"title":"A Systematical Review of the Largest Polymer Flood Project in the World: From Laboratory to Pilots and Field Application","authors":"X. Lu, W. Li, Y. Wei, J. Xu.","doi":"10.2118/210298-pa","DOIUrl":"https://doi.org/10.2118/210298-pa","url":null,"abstract":"\u0000 This paper presents a systematical review of the largest polymer flood project in the world, applied to multilayered, heterogeneous sandstone reservoirs in the giant Daqing Oilfield in China. First, reservoir and fluid characteristics are highlighted to understand the heterogeneity of the reservoir. Next, the project history is summarized, including laboratory studies, pilot tests, commercial tests, and fieldwide applications. Third, typical polymer flood performance and reservoir management measures are presented. Finally, key understandings and lessons learned from more than 50 years of experience are summarized.\u0000 The La-Sa-Xing Field in the Daqing Field Complex contains three types of reservoir sands: Type I sand with high permeability, Type II sand with medium permeability, and Type III sand with low permeability. Polymer flood was studied in the laboratory in the mid 1960s, followed by small-scale pilots beginning in 1972 and industrial-scale pilots starting in 1993, all of which successfully reduced water cut and enhanced oil recovery. Fieldwide application commenced in 1996, targeting the Type I sand. With Type II sand being brought onstream in 2003, the project achieved a peak production of 253,000 BOPD in 2013. Polymer flood reduced water cut by 24.8%. Reservoir management measures, such as zonal injection, profile modification, hydraulic fracturing in low-permeability sand, and injection optimization, proved to be effective. Based on the water-cut performance, production can be divided into four stages: (1) water-cut decline, (2) low water cut, (3) rebound, and (4) water chase. Fit-for-purpose improved-oil-recovery measures were implemented for each stage to improve production performance.\u0000 Key understandings and lessons learned include the following: (1) Polymer flood improves both sweeping and displacing efficiencies; (2) high interlayer permeability contrast leads to low incremental recovery; (3) variable well spacing should be adopted for different reservoir types; (4) adoption of large molecular weight (MW) and large slug size greatly enhances recovery; and (5) salt-resistant polymer is beneficial for produced water reinjection in Type II sand; (6) zonal injection increased swept reservoir zones by 9.8% and swept pay thickness by 10.3%; (7) profile modifications helped improve vertical conformance in injection wells and led to enhanced sweeping efficiency and extended low water-cut stage; and (8) optimization-recommended well spacing for Type I, Type II, and Type III sands is 10–15.5, 5.6–7.6, and 2.5–3.6 acres, respectively.\u0000 In comparison with generally 6–8% incremental recovery by polymer flood in the industry, this project achieved an impressive incremental recovery of 12%, enhancing the oil recovery factor from 40% by primary recovery and waterflood to 52% stock tank oil initially in place (STOIIP). The progressive approach from laboratory experiments through pilots and finally to field application is a best practice for app","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"7 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79479144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sabyasachi Dash, Artur Posenato Garcia, Zoya Heidari
Summary Reliable fluid saturation assessment in organic-rich mudrocks has been a challenge for the oil and gas industry. The composition and spatial distribution of rock components have a significant impact on electrical resistivity and, thus, on hydrocarbon reserves estimates. Clays are typically considered, in resistivity models, to be distributed in laminated or dispersed forms. Additionally, conventional resistivity models do not incorporate conductive components other than brine. Such assumptions can lead to uncertainty in fluid saturation assessment in organic-rich mudrocks. We introduce a well-log-based workflow that quantitatively assimilates the type and spatial distribution of all conductive components to improve reserves evaluation in organic-rich mudrocks and demonstrate its field application in the Eagle Ford, the Woodford, and the Haynesville formations. The introduced workflow consists of an inversion algorithm to estimate geometry-dependent parameters (depolarization factors or geometric model parameters) and water saturation. Inputs to the inversion algorithms include volume concentrations of minerals, estimated from the multimineral analysis. Other inputs are conductivity of rock components and porosity obtained from laboratory experiments and interpretation of well logs. The petrophysical model considers that brine forms the conductive background to which conductive (e.g., clay, pyrite, and kerogen) and nonconductive (e.g., grains and hydrocarbon) components are incorporated. The assumed/estimated petrophysical properties have an impact on the effective conductivity of the rock and thereby can impact the performance of the new resistivity-based method. We applied the new method to different organic-rich mudrock formations to test the universal nature of the method and its efficacy in organic-rich mudrock reservoirs with varying volumetric concentrations of minerals within the rock. We successfully applied the workflow to four wells in the Eagle Ford, the Woodford, and the Haynesville formations. The formation-by-formation inversion showed a variation in geometric model parameters in different petrophysical zones, resulting in improved water saturation estimates. A comparison of the results obtained from the new workflow against those from the Waxman-Smits and Archie models indicated a relative improvement in saturation estimates of 9.5 and 26.3% in the Eagle Ford formation. Similar improvements were noted in the Woodford and the Haynesville formations as well. The improvement can be enhanced in formations with larger fractions of conductive components. The results confirmed that the new workflow improves the reliability of water saturation estimates in organic-rich mudrocks, which has been a challenge for the oil and gas industry. In contrast to conventional techniques, the new method does not need water saturation obtained from core measurements for calibration efforts. All the parameters in the new workflow are geometry- or p
{"title":"A New Workflow for Improved Resistivity-Based Water Saturation Assessment in Organic-Rich Mudrocks: Application to Haynesville, Eagle Ford, and Woodford Formations","authors":"Sabyasachi Dash, Artur Posenato Garcia, Zoya Heidari","doi":"10.2118/214656-pa","DOIUrl":"https://doi.org/10.2118/214656-pa","url":null,"abstract":"Summary Reliable fluid saturation assessment in organic-rich mudrocks has been a challenge for the oil and gas industry. The composition and spatial distribution of rock components have a significant impact on electrical resistivity and, thus, on hydrocarbon reserves estimates. Clays are typically considered, in resistivity models, to be distributed in laminated or dispersed forms. Additionally, conventional resistivity models do not incorporate conductive components other than brine. Such assumptions can lead to uncertainty in fluid saturation assessment in organic-rich mudrocks. We introduce a well-log-based workflow that quantitatively assimilates the type and spatial distribution of all conductive components to improve reserves evaluation in organic-rich mudrocks and demonstrate its field application in the Eagle Ford, the Woodford, and the Haynesville formations. The introduced workflow consists of an inversion algorithm to estimate geometry-dependent parameters (depolarization factors or geometric model parameters) and water saturation. Inputs to the inversion algorithms include volume concentrations of minerals, estimated from the multimineral analysis. Other inputs are conductivity of rock components and porosity obtained from laboratory experiments and interpretation of well logs. The petrophysical model considers that brine forms the conductive background to which conductive (e.g., clay, pyrite, and kerogen) and nonconductive (e.g., grains and hydrocarbon) components are incorporated. The assumed/estimated petrophysical properties have an impact on the effective conductivity of the rock and thereby can impact the performance of the new resistivity-based method. We applied the new method to different organic-rich mudrock formations to test the universal nature of the method and its efficacy in organic-rich mudrock reservoirs with varying volumetric concentrations of minerals within the rock. We successfully applied the workflow to four wells in the Eagle Ford, the Woodford, and the Haynesville formations. The formation-by-formation inversion showed a variation in geometric model parameters in different petrophysical zones, resulting in improved water saturation estimates. A comparison of the results obtained from the new workflow against those from the Waxman-Smits and Archie models indicated a relative improvement in saturation estimates of 9.5 and 26.3% in the Eagle Ford formation. Similar improvements were noted in the Woodford and the Haynesville formations as well. The improvement can be enhanced in formations with larger fractions of conductive components. The results confirmed that the new workflow improves the reliability of water saturation estimates in organic-rich mudrocks, which has been a challenge for the oil and gas industry. In contrast to conventional techniques, the new method does not need water saturation obtained from core measurements for calibration efforts. All the parameters in the new workflow are geometry- or p","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136175337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Summary Low primary and secondary recoveries of original oil in place from modern unconventional reservoirs beg for utilization of tertiary recovery techniques. Enhanced oil recovery (EOR) via cyclic gas injection (“huff ‘n’ puff”) has indeed enhanced the oil recovery in many fields, and many of those projects have also been documented in industry technical papers/case studies. However, the need remains to document new techniques in new reservoirs. This paper documents a small-scale EOR pilot project in the eastern Eagle Ford and shows promising well results. In preparation for the pilot, full characterization of the oil and injection gas was done along with laboratory testing to identify the miscibility properties of the two fluids. Once the injection well facility design was completed, a series of progressively larger gas volumes were injected followed by correspondingly longer production times. Fluids in the returning liquid and gas streams were monitored for compositional changes, and the learnings from each cycle led to adjustments and facility changes to improve the next cycle. After completing five injection/withdrawal cycles in the pilot, a few key observations can be made. The implementation of cyclic gas injection can be both a technical and a commercial success early in its life if reasonable cost controls are implemented and the scope is kept manageable. The process has proved to be both repeatable and predictable, allowing for future economic modeling to be used to help determine timing of subsequent injection cycles. A key component of the success of this pilot has been the availability of small compressors capable of the high pressures required for these projects and learning how to implement cost saving facility designs that still meet high safety standards.
{"title":"Small-Scale EOR Pilot in the Eastern Eagle Ford Boosts Production","authors":"Tim Bozeman, Will Nelle, Quoc Nguyen","doi":"10.2118/209429-pa","DOIUrl":"https://doi.org/10.2118/209429-pa","url":null,"abstract":"Summary Low primary and secondary recoveries of original oil in place from modern unconventional reservoirs beg for utilization of tertiary recovery techniques. Enhanced oil recovery (EOR) via cyclic gas injection (“huff ‘n’ puff”) has indeed enhanced the oil recovery in many fields, and many of those projects have also been documented in industry technical papers/case studies. However, the need remains to document new techniques in new reservoirs. This paper documents a small-scale EOR pilot project in the eastern Eagle Ford and shows promising well results. In preparation for the pilot, full characterization of the oil and injection gas was done along with laboratory testing to identify the miscibility properties of the two fluids. Once the injection well facility design was completed, a series of progressively larger gas volumes were injected followed by correspondingly longer production times. Fluids in the returning liquid and gas streams were monitored for compositional changes, and the learnings from each cycle led to adjustments and facility changes to improve the next cycle. After completing five injection/withdrawal cycles in the pilot, a few key observations can be made. The implementation of cyclic gas injection can be both a technical and a commercial success early in its life if reasonable cost controls are implemented and the scope is kept manageable. The process has proved to be both repeatable and predictable, allowing for future economic modeling to be used to help determine timing of subsequent injection cycles. A key component of the success of this pilot has been the availability of small compressors capable of the high pressures required for these projects and learning how to implement cost saving facility designs that still meet high safety standards.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136175792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Rezaeian, Saman Jahanbakhshi, Kaveh Shaygan, S. Jamshidi
Integrated reservoir-production modeling is a collaborative multidisciplinary tool that can facilitate optimization of oil and gas production operations during the field development planning stage of exploiting subsurface resources. The critical issue with this technique is the excessive computational burden of the large integrated model with many input variables, which has not been effectively addressed to date. This study aims to reduce the computational costs and runtimes associated with the production integration and optimization process from oil fields. To do so, the reservoir and the surface network models of an Iranian oil field were coupled to create an integrated model for the optimization of field parameters to achieve the highest oil production rate. In the first step of simplification, polynomial chaos expansion (PCE) was used to establish a surrogate model from the integrated system. Next, Sobol sensitivity analysis, which is a variance-based, global, and model-free sensitivity analysis technique, was performed to reduce the number of input variables by identifying the most influential variables. Finally, the optimization was implemented using genetic algorithm (GA) on the PCE surrogate model of the integrated system with the most important variables. The results from the case study showed that the integrated model can be replaced with the PCE surrogate model while the accuracy is maintained. Moreover, performing sensitivity analysis considerably decreased the number of input variables for optimization by revealing their significance. The proposed methodology in this study can substantially improve the computational efficiency of the optimization for the integrated reservoir-production system.
{"title":"Optimization of an Integrated Reservoir-Production System Using Polynomial Chaos Expansion and Sobol Sensitivity Analysis","authors":"J. Rezaeian, Saman Jahanbakhshi, Kaveh Shaygan, S. Jamshidi","doi":"10.2118/214329-pa","DOIUrl":"https://doi.org/10.2118/214329-pa","url":null,"abstract":"\u0000 Integrated reservoir-production modeling is a collaborative multidisciplinary tool that can facilitate optimization of oil and gas production operations during the field development planning stage of exploiting subsurface resources. The critical issue with this technique is the excessive computational burden of the large integrated model with many input variables, which has not been effectively addressed to date. This study aims to reduce the computational costs and runtimes associated with the production integration and optimization process from oil fields. To do so, the reservoir and the surface network models of an Iranian oil field were coupled to create an integrated model for the optimization of field parameters to achieve the highest oil production rate. In the first step of simplification, polynomial chaos expansion (PCE) was used to establish a surrogate model from the integrated system. Next, Sobol sensitivity analysis, which is a variance-based, global, and model-free sensitivity analysis technique, was performed to reduce the number of input variables by identifying the most influential variables. Finally, the optimization was implemented using genetic algorithm (GA) on the PCE surrogate model of the integrated system with the most important variables. The results from the case study showed that the integrated model can be replaced with the PCE surrogate model while the accuracy is maintained. Moreover, performing sensitivity analysis considerably decreased the number of input variables for optimization by revealing their significance. The proposed methodology in this study can substantially improve the computational efficiency of the optimization for the integrated reservoir-production system.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"47 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84653248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liquid loading seriously affects gas wells production and even causes gas wells abandonment. Many researchers still focus on correcting a critical liquid-loading flow rate to alleviate these problems. However, they still cannot reasonably be explained. Gas flow rate is higher than the critical liquid-loading flow rate, but liquid loading can still occur. Therefore, until an accurate critical fluid-loading flow rate is discovered, we should monitor the fluid-loading phenomenon to prevent it from affecting production gas wells’ performance. In this work, a fracture liquid-loading monitoring (FLLM) model is proposed and solved for the timely monitoring of fracture liquid-loading (FLL) positions and volume. The Newman product and Green function methods are used to develop and solve the FLLM model. The fracture is discretized into 2nxnz grids to describe an FLL volume and position. The numerical simulation method is used to verify the accuracy of the FLLM model. As a result, four innovative flow regimes, including fracture cavity liquid-loading flow, fracture root liquid-loading flow, transitional flow considering fracture cavity liquid-loading flow, and transitional flow considering fracture root liquid-loading flow, are identified on the pressure response curves. The pressure response of the same gas well at different times is well matched by the model in this paper, and the obtained parameters are more reasonable. The FLLM model can correct for magnified permeability, shortened half-length, and magnified wellbore storage coefficient. In conclusion, the FLLM model is established to monitor FLL, and alert engineers to remove liquid loading on time to prevent water from suddenly rushing into a wellbore and causing gas wells abandonment.
{"title":"Semianalytical Model for Monitoring Fracture Liquid-Loading in Vertical Fractured Gas Wells","authors":"Zhipeng Wang, Z. Ning, Wen-ming Guo","doi":"10.2118/214318-pa","DOIUrl":"https://doi.org/10.2118/214318-pa","url":null,"abstract":"\u0000 Liquid loading seriously affects gas wells production and even causes gas wells abandonment. Many researchers still focus on correcting a critical liquid-loading flow rate to alleviate these problems. However, they still cannot reasonably be explained. Gas flow rate is higher than the critical liquid-loading flow rate, but liquid loading can still occur. Therefore, until an accurate critical fluid-loading flow rate is discovered, we should monitor the fluid-loading phenomenon to prevent it from affecting production gas wells’ performance. In this work, a fracture liquid-loading monitoring (FLLM) model is proposed and solved for the timely monitoring of fracture liquid-loading (FLL) positions and volume. The Newman product and Green function methods are used to develop and solve the FLLM model. The fracture is discretized into 2nxnz grids to describe an FLL volume and position. The numerical simulation method is used to verify the accuracy of the FLLM model. As a result, four innovative flow regimes, including fracture cavity liquid-loading flow, fracture root liquid-loading flow, transitional flow considering fracture cavity liquid-loading flow, and transitional flow considering fracture root liquid-loading flow, are identified on the pressure response curves. The pressure response of the same gas well at different times is well matched by the model in this paper, and the obtained parameters are more reasonable. The FLLM model can correct for magnified permeability, shortened half-length, and magnified wellbore storage coefficient. In conclusion, the FLLM model is established to monitor FLL, and alert engineers to remove liquid loading on time to prevent water from suddenly rushing into a wellbore and causing gas wells abandonment.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"33 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81010820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is well known that waterflooding will create fractures. The created fractures are divided into hydraulic fractures (artificial fractures with proppant) and induced fractures (formed during waterflooding without proppant). There is no proppant in the induced fracture, so it will close as the pressure decreases and extend as the pressure increases. We call it a dynamic induced fracture (DIF). Because of reduced pressure, the DIF will be closed during the shut-in pressure test (well testing). The current conventional well-testing model cannot describe the dynamic behavior of the DIF, resulting in obtaining unreasonable parameters. Thus, this work proposes a DIF model to characterize the DIF behavior during well testing (the injection well will shut in, resulting in a reduction in bottomhole pressure and induced-fracture closure). It is worth noting that a high-permeability zone (HPZ) will be formed by long-time waterflooding and particle transport. The HPZ radius will be greater than or equal to the DIF half-length because the waterflooding pressure can move particles but not necessarily expand the fracture. The point source function method and Duhamel principle are used to obtain the bottomhole pressure response. Numerical simulation methods are used to verify the accuracy of the model. Field cases are matched to demonstrate the practicability of the DIF model. Results show a straight line with a slope greater than the unit, a peak, a straight line with a slope less than one-half, and an upturned straight line on the pressure derivative curve. This peak can move up, down, left, and right to characterize the induced fracture’s dynamic conductivity (DC). The straight line with a slope greater than the unit can illustrate a fracture storage effect. The straight line with a slope less than one-half can describe the closed induced-fracture (CIF) half-length. The upturned straight line can describe the HPZ and reservoir permeability. The obtained parameters will be inaccurate if they are incorrectly identified as other flow regimes. Field cases are matched well to illustrate that identifying the three innovative flow regimes can improve the parameters’ accuracy. In conclusion, the proposed model can characterize the dynamic behavior of induced fracture, better match the field data, and obtain more reasonable reservoir parameters. Finally, two field cases in tight reservoir are discussed to prove its practicality.
{"title":"Pressure-Transient Analysis for Waterflooding with the Influence of Dynamic Induced Fracture in Tight Reservoir: Model and Case Studies","authors":"Zhipeng Wang, Z. Ning, Wen-ming Guo, Qidi Cheng","doi":"10.2118/214321-pa","DOIUrl":"https://doi.org/10.2118/214321-pa","url":null,"abstract":"\u0000 It is well known that waterflooding will create fractures. The created fractures are divided into hydraulic fractures (artificial fractures with proppant) and induced fractures (formed during waterflooding without proppant). There is no proppant in the induced fracture, so it will close as the pressure decreases and extend as the pressure increases. We call it a dynamic induced fracture (DIF). Because of reduced pressure, the DIF will be closed during the shut-in pressure test (well testing). The current conventional well-testing model cannot describe the dynamic behavior of the DIF, resulting in obtaining unreasonable parameters. Thus, this work proposes a DIF model to characterize the DIF behavior during well testing (the injection well will shut in, resulting in a reduction in bottomhole pressure and induced-fracture closure). It is worth noting that a high-permeability zone (HPZ) will be formed by long-time waterflooding and particle transport. The HPZ radius will be greater than or equal to the DIF half-length because the waterflooding pressure can move particles but not necessarily expand the fracture. The point source function method and Duhamel principle are used to obtain the bottomhole pressure response. Numerical simulation methods are used to verify the accuracy of the model. Field cases are matched to demonstrate the practicability of the DIF model. Results show a straight line with a slope greater than the unit, a peak, a straight line with a slope less than one-half, and an upturned straight line on the pressure derivative curve. This peak can move up, down, left, and right to characterize the induced fracture’s dynamic conductivity (DC). The straight line with a slope greater than the unit can illustrate a fracture storage effect. The straight line with a slope less than one-half can describe the closed induced-fracture (CIF) half-length. The upturned straight line can describe the HPZ and reservoir permeability. The obtained parameters will be inaccurate if they are incorrectly identified as other flow regimes. Field cases are matched well to illustrate that identifying the three innovative flow regimes can improve the parameters’ accuracy. In conclusion, the proposed model can characterize the dynamic behavior of induced fracture, better match the field data, and obtain more reasonable reservoir parameters. Finally, two field cases in tight reservoir are discussed to prove its practicality.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"79 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87086785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, large gridblock counts simulation is computationally expensive and time-consuming. This study explores data-driven reduced-order models (ROMs) as an alternative to detailed physics-based simulations. ROMs that use neural networks (NNs) effectively capture nonlinear dependencies and only require available operational data as inputs. NNs are usually labeled black-box tools that are difficult to interpret. On the other hand, physics-informed NNs (PINNs) provide a potential solution to these shortcomings, but they have not yet been applied extensively in petroleum engineering. In this study, a black-oil reservoir simulation model from Volve public data release was used to generate training data for an ROM leveraging long short-term memory (LSTM) NNs’ temporal modeling capacity. Network configurations were explored for their optimal configuration. Monthly oil production was forecast at the individual wells and full-field levels, and then validated against real field data for production history to compare its predictive accuracy against the simulation results. The governing equations for a capacitance resistance model (CRM) were then added to the reservoir-scale NN model as a physics-based constraint and to analyze parameter solutions for efficacy in characterization of the flow field. Data-driven ROM results indicated that a stateless LSTM, with single time lag as input, generated the most accurate predictions. Using a walk-forward validation strategy, the single well ROM increased prediction accuracy by about 95% average when compared with the reservoir simulation and did so with much less computational resources in short time duration. Physical realism of reservoir-scale predictions was improved by the addition of CRM constraint, demonstrated by the removal of negative flow rates. Parameter solutions to the governing equation showed good agreement with the field-scale streamline plots and demonstrated the ROM ability to detect spatial irregularities. These results clearly demonstrate the ease with which ROMs can be built and used to meet or exceed the predictive capabilities of certain time-history production data using the reservoir simulation.
{"title":"Data-Driven Reduced-Order Models for Volve Field Using Reservoir Simulation and Physics-Informed Machine Learning Techniques","authors":"M. Behl, M. Tyagi","doi":"10.2118/214288-pa","DOIUrl":"https://doi.org/10.2118/214288-pa","url":null,"abstract":"\u0000 Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, large gridblock counts simulation is computationally expensive and time-consuming. This study explores data-driven reduced-order models (ROMs) as an alternative to detailed physics-based simulations. ROMs that use neural networks (NNs) effectively capture nonlinear dependencies and only require available operational data as inputs. NNs are usually labeled black-box tools that are difficult to interpret. On the other hand, physics-informed NNs (PINNs) provide a potential solution to these shortcomings, but they have not yet been applied extensively in petroleum engineering.\u0000 In this study, a black-oil reservoir simulation model from Volve public data release was used to generate training data for an ROM leveraging long short-term memory (LSTM) NNs’ temporal modeling capacity. Network configurations were explored for their optimal configuration. Monthly oil production was forecast at the individual wells and full-field levels, and then validated against real field data for production history to compare its predictive accuracy against the simulation results. The governing equations for a capacitance resistance model (CRM) were then added to the reservoir-scale NN model as a physics-based constraint and to analyze parameter solutions for efficacy in characterization of the flow field.\u0000 Data-driven ROM results indicated that a stateless LSTM, with single time lag as input, generated the most accurate predictions. Using a walk-forward validation strategy, the single well ROM increased prediction accuracy by about 95% average when compared with the reservoir simulation and did so with much less computational resources in short time duration. Physical realism of reservoir-scale predictions was improved by the addition of CRM constraint, demonstrated by the removal of negative flow rates. Parameter solutions to the governing equation showed good agreement with the field-scale streamline plots and demonstrated the ROM ability to detect spatial irregularities. These results clearly demonstrate the ease with which ROMs can be built and used to meet or exceed the predictive capabilities of certain time-history production data using the reservoir simulation.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83896915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Isah, M. Mahmoud, M. Kamal, M. Arif, M. A. Jawad
Anhydrite (CaSO4) is a chemically reactive rock/mineral found predominantly as a constituent of carbonates. The main constituents of anhydrite are calcium and sulfate ions. The presence of anhydrite, its distribution, and the associated anhydrite-fluid interactions are important to precisely evaluate the effectiveness of oil recovery techniques. While anhydrite dissolution is the key interaction mechanism in anhydrite-rich rocks, its presence may also lead to complex rock wetting behavior. The underpinning logic is that pure anhydrite is strongly water-wet, while pure calcite and dolomite are somewhat intermediate to weakly oil-wet, thus the question remains unclear as to what the wettability would be of anhydrite and calcite, and anhydrite and dolomite combinations. Moreover, because anhydrite is negatively charged while dolomite and calcite in formation water (FW) are positively charged, depending on the mixture composition, pH, and brine type, it is not clear what the charge would be of a combination of anhydrite-calcite or anhydrite-dolomite, and, consequently, what the wetting behavior of calcite and dolomite would be due to anhydrite presence. Therefore, this research explores the effect of anhydrite mineral on carbonate wetting characteristics. The effect of mineralogical heterogeneity, specifically the presence of anhydrite minerals in calcite and dolomite wettability, is investigated across a range of scales. The results show that anhydrite dissolution occurs in deionized (DI) water, seawater (SW), and FW as evident from the general increase in sulfate ions concentration with increased anhydrite content in the anhydrite-carbonate system. We also found that zeta potential demonstrates an unstable colloidal system, which is indicated by near-zero and low zeta potential values (less than ±10) of the anhydrite-carbonate-brine systems. It also shows a nonmonotonic wetting behavior with brine salinity and pH variations. Accordingly, the zeta potential is not a general and valid candidate to justify the wettability behavior of heterogeneous carbonates. However, based on flotation and contact angle techniques of wettability estimation, anhydrite presence has the tendency to alter the wetting state of anhydrite-carbonate-brine-oil systems to more water-wet. Thus, findings from this research will provide answers to the question of how the mineralogy affects the wetting characteristics of carbonates. What will be the changes in carbonate wetting behavior with mineralogical heterogeneity? Specifically, what would be the wettability of calcite-anhydrite and dolomite-anhydrite combinations? This research therefore provides a systematic investigation of rock/fluid interactions and their implications on wettability and ultimate recovery of oil at different range scales. The findings from this study will significantly enhance our knowledge of fluid-rock interactions, in particular, anhydrite-rich carbonate wetting behavior, thereby reducing the uncert
{"title":"Multiscale Wettability Characterization of Anhydrite-Rich Carbonate Rocks: Insights into Zeta Potential, Flotation, and Contact Angle Measurements","authors":"A. Isah, M. Mahmoud, M. Kamal, M. Arif, M. A. Jawad","doi":"10.2118/214324-pa","DOIUrl":"https://doi.org/10.2118/214324-pa","url":null,"abstract":"\u0000 Anhydrite (CaSO4) is a chemically reactive rock/mineral found predominantly as a constituent of carbonates. The main constituents of anhydrite are calcium and sulfate ions. The presence of anhydrite, its distribution, and the associated anhydrite-fluid interactions are important to precisely evaluate the effectiveness of oil recovery techniques. While anhydrite dissolution is the key interaction mechanism in anhydrite-rich rocks, its presence may also lead to complex rock wetting behavior. The underpinning logic is that pure anhydrite is strongly water-wet, while pure calcite and dolomite are somewhat intermediate to weakly oil-wet, thus the question remains unclear as to what the wettability would be of anhydrite and calcite, and anhydrite and dolomite combinations. Moreover, because anhydrite is negatively charged while dolomite and calcite in formation water (FW) are positively charged, depending on the mixture composition, pH, and brine type, it is not clear what the charge would be of a combination of anhydrite-calcite or anhydrite-dolomite, and, consequently, what the wetting behavior of calcite and dolomite would be due to anhydrite presence. Therefore, this research explores the effect of anhydrite mineral on carbonate wetting characteristics. The effect of mineralogical heterogeneity, specifically the presence of anhydrite minerals in calcite and dolomite wettability, is investigated across a range of scales.\u0000 The results show that anhydrite dissolution occurs in deionized (DI) water, seawater (SW), and FW as evident from the general increase in sulfate ions concentration with increased anhydrite content in the anhydrite-carbonate system. We also found that zeta potential demonstrates an unstable colloidal system, which is indicated by near-zero and low zeta potential values (less than ±10) of the anhydrite-carbonate-brine systems. It also shows a nonmonotonic wetting behavior with brine salinity and pH variations. Accordingly, the zeta potential is not a general and valid candidate to justify the wettability behavior of heterogeneous carbonates. However, based on flotation and contact angle techniques of wettability estimation, anhydrite presence has the tendency to alter the wetting state of anhydrite-carbonate-brine-oil systems to more water-wet. Thus, findings from this research will provide answers to the question of how the mineralogy affects the wetting characteristics of carbonates. What will be the changes in carbonate wetting behavior with mineralogical heterogeneity? Specifically, what would be the wettability of calcite-anhydrite and dolomite-anhydrite combinations? This research therefore provides a systematic investigation of rock/fluid interactions and their implications on wettability and ultimate recovery of oil at different range scales. The findings from this study will significantly enhance our knowledge of fluid-rock interactions, in particular, anhydrite-rich carbonate wetting behavior, thereby reducing the uncert","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"7 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89392384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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