Li Tao, C. Qiang, S. Qiang, Han Weiye, Huang Shouzhi, Liu Longda
Wellbore integrity was a thorny issue in China since hundreds of thousands of wells needed to be repaired annually, leading to cost increase and production delay. This problem became more excruciating in the long horizontal wellbore considering the high risk of downhole tools stuck. So far casing damage in the horizontal wellbore was either chemically plugged or separated by bridge plug, posing huge threat to the reservoir and future operations. Solid expandable tubular was a rising star in the downhole workover programme, its application in the horizontal wellbore would further enrich our technical warehouse to enhance the wellbore integrity. In this paper, the challenges of horizontal wellbore workover operations were presented; the expandable technology was introduced and then innovated the adapt to the challenges, finally its field operation was described and relevant summaries of lessons were demonstrated. The results indicated that as the number of horizontal well increased dramatically, problems such as casing damage, sand plugging occurred more frequently, downhole tools usually needed additional force to forward in the horizontal part to finish well logging or other activities, casing integrity was necessary to prevent the stuck of downhole tools. Solid expandable tubular was a field proven technology, in order to overcome issues like tripping in process, expansion hurdles in the irregular well trajectory, the structure of solid expandable tubular was optimized radically. First the material of tubular was changed to achieve N80 steel grade after expansion, the OD of tubular was adjusted to maximize the annulus space between the casing and the tubular. Second the thread was restructured the further enhance its strength. Finally the rubber outside the tubular was innovated to prevent being worn out as much as possible during its friction with the horizontal wellbore. Field operation was carried out in west China, 18m length of expandable tubular was deliver into the end of 327m horizontal wellbore, expansion process was started and 41MPa expansion force was recorded. This paper served to enrich our capabilities to deal with workover operation in the horizontal wellbore, its content helped better understand the principle, procedure and potential of this enable technology.
{"title":"Application of Downhole Well Integrity Technology in the Petroleum Industry, A Case Study in the Horizontal Wellbore","authors":"Li Tao, C. Qiang, S. Qiang, Han Weiye, Huang Shouzhi, Liu Longda","doi":"10.2118/195949-ms","DOIUrl":"https://doi.org/10.2118/195949-ms","url":null,"abstract":"\u0000 Wellbore integrity was a thorny issue in China since hundreds of thousands of wells needed to be repaired annually, leading to cost increase and production delay. This problem became more excruciating in the long horizontal wellbore considering the high risk of downhole tools stuck. So far casing damage in the horizontal wellbore was either chemically plugged or separated by bridge plug, posing huge threat to the reservoir and future operations. Solid expandable tubular was a rising star in the downhole workover programme, its application in the horizontal wellbore would further enrich our technical warehouse to enhance the wellbore integrity.\u0000 In this paper, the challenges of horizontal wellbore workover operations were presented; the expandable technology was introduced and then innovated the adapt to the challenges, finally its field operation was described and relevant summaries of lessons were demonstrated.\u0000 The results indicated that as the number of horizontal well increased dramatically, problems such as casing damage, sand plugging occurred more frequently, downhole tools usually needed additional force to forward in the horizontal part to finish well logging or other activities, casing integrity was necessary to prevent the stuck of downhole tools.\u0000 Solid expandable tubular was a field proven technology, in order to overcome issues like tripping in process, expansion hurdles in the irregular well trajectory, the structure of solid expandable tubular was optimized radically. First the material of tubular was changed to achieve N80 steel grade after expansion, the OD of tubular was adjusted to maximize the annulus space between the casing and the tubular. Second the thread was restructured the further enhance its strength. Finally the rubber outside the tubular was innovated to prevent being worn out as much as possible during its friction with the horizontal wellbore. Field operation was carried out in west China, 18m length of expandable tubular was deliver into the end of 327m horizontal wellbore, expansion process was started and 41MPa expansion force was recorded.\u0000 This paper served to enrich our capabilities to deal with workover operation in the horizontal wellbore, its content helped better understand the principle, procedure and potential of this enable technology.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"10 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91481267","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}
R. Bratvold, Erlend Mohus, D. Petutschnig, E. Bickel
The oil & gas industry uses production forecasts to make a number of decisions as mundane as whether to change the choke setting on a well, or as significant as whether to develop a field. As these forecasts are being used to develop cashflow predictions and value and decision metrics such as Net Present Value and Internal Rate of Return, their quality is essential for making good decision. Thus, forecasting skills are important for value creation and we should keep track of whether production forecasts are accurate and free from bias. In this paper we compare probabilistic production forecasts at the time of the development FID with the actual annual production to assess whether the forecasts are biased; i.e., either optimistic, overconfident, or both. While biases in time and cost estimates in the exploration & production industry are well documented, probabilistic production forecasts have yet to be the focus of a major study. The main reason for this is that production forecasts for exploration & production development projects are not publicly available. Without access to such estimates, the quality of the forecasts cannot be evaluated. Drawing on the Norwegian Petroleum Directorates (NPD) extensive database, annual production forecasts, given at time of project sanction (FID), for 56 fields in the 1995 – 2017 period, have been compared with actual annual production from the same fields. The NPD guidelines specify that the operators should report the annual mean and P10/90-percentiles for the projected life of the field at the time of the FID; that is, the forecasts should be probabilistic. The actual annual production from the fields was statistically compared with the forecast to investigate if the forecasts were biased and to assess the financial impact of such biases. This paper presents the results from the first public study of the quality of probabilistic production forecasts. The main conclusions are that production forecasts that are being used at the FID for E&P development projects are both optimistic and overconfident. As production forecasts form the basis for the main investment decision in the life of a field, biased forecasts will lead to poor decisions and to loss of value.
{"title":"Production Forecasting: Optimistic and Overconfident – Over and Over Again","authors":"R. Bratvold, Erlend Mohus, D. Petutschnig, E. Bickel","doi":"10.2118/195914-ms","DOIUrl":"https://doi.org/10.2118/195914-ms","url":null,"abstract":"\u0000 The oil & gas industry uses production forecasts to make a number of decisions as mundane as whether to change the choke setting on a well, or as significant as whether to develop a field. As these forecasts are being used to develop cashflow predictions and value and decision metrics such as Net Present Value and Internal Rate of Return, their quality is essential for making good decision. Thus, forecasting skills are important for value creation and we should keep track of whether production forecasts are accurate and free from bias.\u0000 In this paper we compare probabilistic production forecasts at the time of the development FID with the actual annual production to assess whether the forecasts are biased; i.e., either optimistic, overconfident, or both.\u0000 While biases in time and cost estimates in the exploration & production industry are well documented, probabilistic production forecasts have yet to be the focus of a major study. The main reason for this is that production forecasts for exploration & production development projects are not publicly available. Without access to such estimates, the quality of the forecasts cannot be evaluated.\u0000 Drawing on the Norwegian Petroleum Directorates (NPD) extensive database, annual production forecasts, given at time of project sanction (FID), for 56 fields in the 1995 – 2017 period, have been compared with actual annual production from the same fields. The NPD guidelines specify that the operators should report the annual mean and P10/90-percentiles for the projected life of the field at the time of the FID; that is, the forecasts should be probabilistic. The actual annual production from the fields was statistically compared with the forecast to investigate if the forecasts were biased and to assess the financial impact of such biases.\u0000 This paper presents the results from the first public study of the quality of probabilistic production forecasts. The main conclusions are that production forecasts that are being used at the FID for E&P development projects are both optimistic and overconfident. As production forecasts form the basis for the main investment decision in the life of a field, biased forecasts will lead to poor decisions and to loss of value.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91099942","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}
A mechanistic approach for calculation of oil-gas capillary pressure curves and relative permeabilities in unconventional reservoirs is presented. The approach accounts for reservoir fluid composition, contact angle wettability and pore size distribution of each specific reservoir and generates a unique set of relative permeability curves based on those inputs. This allows calculation of curves in reservoirs where historical production data is limited. Phase behavior calculations are computed by coupling the Peng-Robinson equation of state and the Young-Laplace capillary pressure model. This coupling allows for inclusion of the effect of confinement of reservoir fluids on volumetric and transport properties. The reservoir is modeled as a bundle of tubes with diameters representative of the pore size distribution found in the reservoir. A multi-step depletion is modeled followed by gas injection and a secondary depletion. Separate capillary pressure results are obtained for each part of the process. After the capillary pressure curves are generated, an integration is performed on the capillary results to generate a set of relative permeability curves following the Nakornthap and Evans method (1986). The multi-step process is used to allow recalculation of the relative permeability curves as the reservoir fluid composition changes due to the initial depletion and then secondary gas injection.The approach yields a unique set of relative permeability results for each set of input parameters.The mechanistic approach is demonstrated on two different oil compositions, a black oil sample and a volatile oil. For each of the oil compositions, two different injection gasses are evaluated (methane and carbon dioxide). The intermediate calculations are summarized and the final permeability results are included in the paper. The results show that for both oil samples evaluated, the gas injection results in an increase in oil relative permeability. Carbon dioxide is more effective at increasing the oil relative permeability than methane for both oil samples. This suggests that carbon dioxide could be an effective option for enhanced oil recovery operations in unconventional reservoirs. A unique element of the approach presented is that the calculation of relative permeability curves for the initial reservoir depletion is immediately followed by the calculation of new relative permeability curves as the reservoir composition changes due to gas injection. This allows prediction of relative permeability results in an unconventional reservoir for both the initial reservoir depletion and also for hypothetical enhanced oil recovery operations. Since the model can be run quickly and repeatedly, sensitivity analyses can be performed on the permeability curves as a function of initial reservoir conditions and injection gas compositions and amounts.
{"title":"A Mechanistic Approach for Calculating Oil-Gas Relative Permeability Curves in Unconventional Reservoirs","authors":"Bartosz Czernia, M. Barrufet","doi":"10.2118/196051-ms","DOIUrl":"https://doi.org/10.2118/196051-ms","url":null,"abstract":"\u0000 A mechanistic approach for calculation of oil-gas capillary pressure curves and relative permeabilities in unconventional reservoirs is presented. The approach accounts for reservoir fluid composition, contact angle wettability and pore size distribution of each specific reservoir and generates a unique set of relative permeability curves based on those inputs. This allows calculation of curves in reservoirs where historical production data is limited.\u0000 Phase behavior calculations are computed by coupling the Peng-Robinson equation of state and the Young-Laplace capillary pressure model. This coupling allows for inclusion of the effect of confinement of reservoir fluids on volumetric and transport properties.\u0000 The reservoir is modeled as a bundle of tubes with diameters representative of the pore size distribution found in the reservoir. A multi-step depletion is modeled followed by gas injection and a secondary depletion. Separate capillary pressure results are obtained for each part of the process. After the capillary pressure curves are generated, an integration is performed on the capillary results to generate a set of relative permeability curves following the Nakornthap and Evans method (1986).\u0000 The multi-step process is used to allow recalculation of the relative permeability curves as the reservoir fluid composition changes due to the initial depletion and then secondary gas injection.The approach yields a unique set of relative permeability results for each set of input parameters.The mechanistic approach is demonstrated on two different oil compositions, a black oil sample and a volatile oil. For each of the oil compositions, two different injection gasses are evaluated (methane and carbon dioxide). The intermediate calculations are summarized and the final permeability results are included in the paper. The results show that for both oil samples evaluated, the gas injection results in an increase in oil relative permeability. Carbon dioxide is more effective at increasing the oil relative permeability than methane for both oil samples. This suggests that carbon dioxide could be an effective option for enhanced oil recovery operations in unconventional reservoirs.\u0000 A unique element of the approach presented is that the calculation of relative permeability curves for the initial reservoir depletion is immediately followed by the calculation of new relative permeability curves as the reservoir composition changes due to gas injection. This allows prediction of relative permeability results in an unconventional reservoir for both the initial reservoir depletion and also for hypothetical enhanced oil recovery operations. Since the model can be run quickly and repeatedly, sensitivity analyses can be performed on the permeability curves as a function of initial reservoir conditions and injection gas compositions and amounts.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90242689","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}
G. Ugueto, F. Todea, Talib Daredia, M. Wojtaszek, P. Huckabee, A. Reynolds, C. Laing, J. Chavarria
The use of Distributed Acoustic Sensing for Strain Fronts (DAS-SF) is gaining popularity as one of the tools to help characterize the geometries of hydraulic fracs and to assess the far-field efficiencies of stimulation operations in Unconventional Reservoirs. These strain fronts are caused by deformation of the rock during hydraulic fracture stimulation (HFS) which produces a characteristic strain signature measurable by interrogating a glass fiber in wells instrumented with a fiber optic (FO) cable cemented behind casing. This DAS application was first developed by Shell and OptaSense from datasets acquired in the Groundbirch Montney in Canada. In this paper we show examples of DAS-SF in wells stimulated for a variety of completion systems: plug-and-perforating (PnP), open hole packer sleeves (OHPS), as well as, data from a well completed via both ball-activated cemented single point entry sleeves (Ba-cSPES) and coil-tubing activated cemented single point entry sleeves (CTa-cSPES). By measuring the strain fronts during stimulation from nearby offset wells, it was observed that most stimulated stages produced far-field strain gradient responses in the monitor well. When mapped in space, the strain responses were found to agree with and confirm the dominant planar fracture geometry proposed for the Montney, with hydraulic fractures propagating in a direction perpendicular to the minimum stress. However; several unexpected and inconsistent off-azimuth events were also observed during the offset well stimulations in which the strain fronts were detected at locations already stimulated by previous stages. Through further integration and the analysis of multiple data sources, it was discovered that these strain events corresponded with stage isolation defects in the stimulated well, leading to "re-stimulation" of prior fracs and inefficient resource development. The strain front monitoring in the Montney has provided greater confidence in the planar fracture geometry hypothesis for this formation. The high resolution frac geometry information provided by DAS-SF away from the wellbore in the far-field has also enabled us to improve stage offsetting and well azimuth strategies. In addition, identifying the re-stimulation and loss of resource access that occurs with poor stage isolation also shows opportunities for improvement in future completion programs. This in turn, should allow us to optimize operational decisions to more effectively access the intended resource volumes. These datasets show how monitoring high-resolution deformation via FO combined with the integration of other data can provide high confidence insights about stimulation efficiency, frac geometry and well construction defects not available via other means.
{"title":"Can You Feel the Strain? DAS Strain Fronts for Fracture Geometry in the BC Montney, Groundbirch","authors":"G. Ugueto, F. Todea, Talib Daredia, M. Wojtaszek, P. Huckabee, A. Reynolds, C. Laing, J. Chavarria","doi":"10.2118/195943-ms","DOIUrl":"https://doi.org/10.2118/195943-ms","url":null,"abstract":"\u0000 The use of Distributed Acoustic Sensing for Strain Fronts (DAS-SF) is gaining popularity as one of the tools to help characterize the geometries of hydraulic fracs and to assess the far-field efficiencies of stimulation operations in Unconventional Reservoirs. These strain fronts are caused by deformation of the rock during hydraulic fracture stimulation (HFS) which produces a characteristic strain signature measurable by interrogating a glass fiber in wells instrumented with a fiber optic (FO) cable cemented behind casing. This DAS application was first developed by Shell and OptaSense from datasets acquired in the Groundbirch Montney in Canada. In this paper we show examples of DAS-SF in wells stimulated for a variety of completion systems: plug-and-perforating (PnP), open hole packer sleeves (OHPS), as well as, data from a well completed via both ball-activated cemented single point entry sleeves (Ba-cSPES) and coil-tubing activated cemented single point entry sleeves (CTa-cSPES). By measuring the strain fronts during stimulation from nearby offset wells, it was observed that most stimulated stages produced far-field strain gradient responses in the monitor well. When mapped in space, the strain responses were found to agree with and confirm the dominant planar fracture geometry proposed for the Montney, with hydraulic fractures propagating in a direction perpendicular to the minimum stress. However; several unexpected and inconsistent off-azimuth events were also observed during the offset well stimulations in which the strain fronts were detected at locations already stimulated by previous stages. Through further integration and the analysis of multiple data sources, it was discovered that these strain events corresponded with stage isolation defects in the stimulated well, leading to \"re-stimulation\" of prior fracs and inefficient resource development. The strain front monitoring in the Montney has provided greater confidence in the planar fracture geometry hypothesis for this formation. The high resolution frac geometry information provided by DAS-SF away from the wellbore in the far-field has also enabled us to improve stage offsetting and well azimuth strategies. In addition, identifying the re-stimulation and loss of resource access that occurs with poor stage isolation also shows opportunities for improvement in future completion programs. This in turn, should allow us to optimize operational decisions to more effectively access the intended resource volumes. These datasets show how monitoring high-resolution deformation via FO combined with the integration of other data can provide high confidence insights about stimulation efficiency, frac geometry and well construction defects not available via other means.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84347306","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}
Successful implementation of a recovery project in a fractured reservoir requires that the matrix fracture mass transfer is well understood. As a consequence, several processes involved in the mass transfer have been widely studied along time on account of its impact on the fractured porous media. Capillary imbibition is one of these significant phenomena and is considered through wettability in several mass transfer formulations (also called transfer functions) as the main mass driving force between matrix and fracture. This paper presents simulated results of waterflooding tests in a fractured core-plug model, evaluating the influence of wettability and flow rate alteration on the matrix-fracture mass transfer. The methodology applied is divided into three main parts. Initially, a single-porosity core model with an induced longitudinally fracture at laboratory scale is recreated. Secondly, three synthetically wettability scenarios (water-wet, intermediate-wet, and oil-wet) and two flow rates (0.1 and 1 cm³/min) are selected and applied in the core-plug model to perform, as a third step, a sensitivity analysis in terms of oil recovery factor, water cut and water saturation. Results show that the increase of rock preference for water leads to the highest oil recovery factors at low and high-water injection rate, benefiting mainly from the spontaneous imbibition of water. The spontaneous imbibition in these cases is notably critical in the low-rate scenario, due to its larger contact time with water and rock. However, the increment on production may not be economically feasible, because of the long time (high injected pore volumes) needed to get this increase. In contrast, intermediate and oil-wet scenarios exhibit low oil sweep and displacement efficiency at both water injection rates. Accordingly, these scenarios reach water breakthrough quickly and exhibit a less accentuated tendency to water saturation alterations if compared with the water-wet scenario. Results also show a good agreement between the water saturation distributions along the length and the effect of the induced fracture, validating its use. In a numerical simulation study, this work shows the importance of close interaction between the wettability, flow rate changes, and the parameters that control matrix-fracture mass transfer. At last, the significance of these sensitive parameters is also demonstrated.
{"title":"Wettability and Flow Rate Effects on Mass Transfer for Simulation of Fractured Reservoirs","authors":"S. A. R. Soler","doi":"10.2118/199905-stu","DOIUrl":"https://doi.org/10.2118/199905-stu","url":null,"abstract":"\u0000 Successful implementation of a recovery project in a fractured reservoir requires that the matrix fracture mass transfer is well understood. As a consequence, several processes involved in the mass transfer have been widely studied along time on account of its impact on the fractured porous media. Capillary imbibition is one of these significant phenomena and is considered through wettability in several mass transfer formulations (also called transfer functions) as the main mass driving force between matrix and fracture. This paper presents simulated results of waterflooding tests in a fractured core-plug model, evaluating the influence of wettability and flow rate alteration on the matrix-fracture mass transfer. The methodology applied is divided into three main parts. Initially, a single-porosity core model with an induced longitudinally fracture at laboratory scale is recreated. Secondly, three synthetically wettability scenarios (water-wet, intermediate-wet, and oil-wet) and two flow rates (0.1 and 1 cm³/min) are selected and applied in the core-plug model to perform, as a third step, a sensitivity analysis in terms of oil recovery factor, water cut and water saturation. Results show that the increase of rock preference for water leads to the highest oil recovery factors at low and high-water injection rate, benefiting mainly from the spontaneous imbibition of water. The spontaneous imbibition in these cases is notably critical in the low-rate scenario, due to its larger contact time with water and rock. However, the increment on production may not be economically feasible, because of the long time (high injected pore volumes) needed to get this increase. In contrast, intermediate and oil-wet scenarios exhibit low oil sweep and displacement efficiency at both water injection rates. Accordingly, these scenarios reach water breakthrough quickly and exhibit a less accentuated tendency to water saturation alterations if compared with the water-wet scenario. Results also show a good agreement between the water saturation distributions along the length and the effect of the induced fracture, validating its use.\u0000 In a numerical simulation study, this work shows the importance of close interaction between the wettability, flow rate changes, and the parameters that control matrix-fracture mass transfer. At last, the significance of these sensitive parameters is also demonstrated.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81782772","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}
J. Hirschmiller, A. Biryukov, B. Groulx, Brian Emmerson, Scott Quinell
This machine learning study incorporates geoscience and engineering data to characterize which geological, reservoir and completion data contribute most significantly to well production performance. A better understanding of the key factors that predict well performance is essential in assessing the commercial viability of exploration and development, in the optimization of capital spending to increase rates of return, and in reserve and resource evaluations. Machine learning models provide an objective, analytical means to interpret large, complex datasets. Generally, such models demand large databases of consistently evaluated data. As geological data is interpretive, often varying from one geologist to another, or from one pool to another, it can be difficult to incorporate geological data into regional machine learning models. Consequently, efforts to use machine learning in the oil and gas industry to predict well performance are often focused exclusively on engineering completion technology. However, this case study has utilized a regional geological Spirit River database with consistent petrophysical evaluation methodology across the entire play. This geological database is complemented with public completion and fracture data and production data to build predictive models using inputs from all subsurface disciplines. Redundancies in the data were identified and removed. Features explaining a significant proportion of the variance in production were also removed if their effect was captured by more fundamental, correlated features that were more straightforward to interpret. The dataset was distilled to 13 key features providing predictions with a similar precision to those obtained using the full-featured dataset. The thirteen features in this case study are a combination of geological, reservoir and completion data, underlining that an approach integrating both geoscience and engineering data is vital to predicting and optimizing well performance accurately for future wells.
{"title":"The Importance of Integrating Subsurface Disciplines with Machine Learning when Predicting and Optimizing Well Performance – Case Study from the Spirit River Formation","authors":"J. Hirschmiller, A. Biryukov, B. Groulx, Brian Emmerson, Scott Quinell","doi":"10.2118/196089-ms","DOIUrl":"https://doi.org/10.2118/196089-ms","url":null,"abstract":"\u0000 This machine learning study incorporates geoscience and engineering data to characterize which geological, reservoir and completion data contribute most significantly to well production performance. A better understanding of the key factors that predict well performance is essential in assessing the commercial viability of exploration and development, in the optimization of capital spending to increase rates of return, and in reserve and resource evaluations.\u0000 Machine learning models provide an objective, analytical means to interpret large, complex datasets. Generally, such models demand large databases of consistently evaluated data. As geological data is interpretive, often varying from one geologist to another, or from one pool to another, it can be difficult to incorporate geological data into regional machine learning models. Consequently, efforts to use machine learning in the oil and gas industry to predict well performance are often focused exclusively on engineering completion technology. However, this case study has utilized a regional geological Spirit River database with consistent petrophysical evaluation methodology across the entire play. This geological database is complemented with public completion and fracture data and production data to build predictive models using inputs from all subsurface disciplines.\u0000 Redundancies in the data were identified and removed. Features explaining a significant proportion of the variance in production were also removed if their effect was captured by more fundamental, correlated features that were more straightforward to interpret. The dataset was distilled to 13 key features providing predictions with a similar precision to those obtained using the full-featured dataset.\u0000 The thirteen features in this case study are a combination of geological, reservoir and completion data, underlining that an approach integrating both geoscience and engineering data is vital to predicting and optimizing well performance accurately for future wells.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"2012 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86355689","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}
Wei Chen, Yuelin Shen, Zhengxin Zhang, C. Bogath, Richard Harmer
Mechanical specific energy (MSE) has been widely used in the industry to monitor drilling efficiency. However, it does not give detailed information about energy flow in the drilling system and lacks the resolution to identify the root cause of energy loss. The drilling operation is a dynamic process. Energy input may be from a surface-drive system (top drive or rotary table) or a mud motor placed downhole. In a perfect world, all of the energy is used to drill the rock. However, some of the input energy may reside in the drillstring as strain and kinetic energy due to the deformation and motion of the drillstring. Drilling energy is dissipated due to shock, vibration, fluid damping, and frictional contact between the drillstring and wellbore. A novel method has been developed to calculate the drilling energy flow in the drillstring and to enable better drilling energy management by maximizing useful energy consumption and reducing energy waste. The method provides a new way to understand and improve drilling efficiency. The method is based on an advanced transient drilling dynamics model which simulates the full drilling system from surface to bit. The entire drillstring is meshed using 3D beam elements, and its dynamic response history is solved by the finite element method (FEM). The energy input can be calculated from surface drilling parameters, such as torque, rotation speed, flow rate, and motor differential pressure. With the simulated history of forces and dynamics of the drillstring, the corresponding strain energy and kinetic energy of the drillstring can be evaluated. The detailed cutting structure model can provide insight on the energy amount consumed by the rock cutting action of the bit and reamer. Putting all the components together leads to a holistic calculation workflow of drilling energy. Field case studies were conducted to examine the effectiveness of this method. The studies showed the drillstring strain energy and kinetic energy are good performance indicators for drillstring reliability and stability because these energy variables reflect the severity of loading and vibration in the drillstring. The energy variables possess clear signatures for interpretation of different downhole vibration modes. Currently, the drilling efficiency is normally evaluated by MSE, which represents the amount of energy needed to remove a unit volume of rock using the surface drilling data. In this study, the energy loss is calculated to understand the percentage of input energy dissipated due to the interaction of the drillstring with the environment. In contrast to MSE, the calculation provides a more direct and detailed measurement of drilling efficiency. It gives a methodology for understanding detailed energy flow in the drilling system under different drilling vibration modes. It can be applied to bit selection, bottomhole assembly (BHA) design, and drilling parameter optimization to achieve better drilling energy management and imp
{"title":"Understand Drilling System Energy Beyond MSE","authors":"Wei Chen, Yuelin Shen, Zhengxin Zhang, C. Bogath, Richard Harmer","doi":"10.2118/196050-ms","DOIUrl":"https://doi.org/10.2118/196050-ms","url":null,"abstract":"\u0000 Mechanical specific energy (MSE) has been widely used in the industry to monitor drilling efficiency. However, it does not give detailed information about energy flow in the drilling system and lacks the resolution to identify the root cause of energy loss. The drilling operation is a dynamic process. Energy input may be from a surface-drive system (top drive or rotary table) or a mud motor placed downhole. In a perfect world, all of the energy is used to drill the rock. However, some of the input energy may reside in the drillstring as strain and kinetic energy due to the deformation and motion of the drillstring. Drilling energy is dissipated due to shock, vibration, fluid damping, and frictional contact between the drillstring and wellbore. A novel method has been developed to calculate the drilling energy flow in the drillstring and to enable better drilling energy management by maximizing useful energy consumption and reducing energy waste. The method provides a new way to understand and improve drilling efficiency.\u0000 The method is based on an advanced transient drilling dynamics model which simulates the full drilling system from surface to bit. The entire drillstring is meshed using 3D beam elements, and its dynamic response history is solved by the finite element method (FEM). The energy input can be calculated from surface drilling parameters, such as torque, rotation speed, flow rate, and motor differential pressure. With the simulated history of forces and dynamics of the drillstring, the corresponding strain energy and kinetic energy of the drillstring can be evaluated. The detailed cutting structure model can provide insight on the energy amount consumed by the rock cutting action of the bit and reamer. Putting all the components together leads to a holistic calculation workflow of drilling energy.\u0000 Field case studies were conducted to examine the effectiveness of this method. The studies showed the drillstring strain energy and kinetic energy are good performance indicators for drillstring reliability and stability because these energy variables reflect the severity of loading and vibration in the drillstring. The energy variables possess clear signatures for interpretation of different downhole vibration modes. Currently, the drilling efficiency is normally evaluated by MSE, which represents the amount of energy needed to remove a unit volume of rock using the surface drilling data. In this study, the energy loss is calculated to understand the percentage of input energy dissipated due to the interaction of the drillstring with the environment. In contrast to MSE, the calculation provides a more direct and detailed measurement of drilling efficiency. It gives a methodology for understanding detailed energy flow in the drilling system under different drilling vibration modes. It can be applied to bit selection, bottomhole assembly (BHA) design, and drilling parameter optimization to achieve better drilling energy management and imp","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85878272","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}
Ahmed Alshmakhy, Khadija Al Daghar, Sameer Punnapala, S. Alshehhi, A. Amara, G. Makin, Stephen Faux
Majority of the world's gas lifted wells are under-optimized owing to changing reservoir conditions and fluid composition. The gas lift valve (GLV) calibration is required with changing conditions. Apart from that, an allowance needs to be kept so that the valve change remains valid for longer time. Compounding this, when adjusting gas lift parameters, it was not easy for the gas lift operator to make data-driven decisions to assure continuous maximized production. These challenges are further amplified with dual completion strings: fluctuating casing pressure; unpredictable temperatures due to the proximity of the two strings; and inability to individually control the injection rates to each string. String dedicated to the formation with lower productivity and reservoir pressure tends to "rob" gas from other string. Operating philosophy in such cases end up producing from one string. Production optimization in such cases requires frequent intervention with attendant costs and risks thus presents an opportunity to re-imagine gas lift well design. ADNOC in collaboration with Silverwell developed a Digital Intelligent Artificial Lift (DIAL) system, which consists of multiple port mandrels to be placed at GLV depths. These mandrels are connetced to the surface operating system with a single electrical cable. The ports can be selectively opened or closed by sending an electric signal from the surface unit. In addition, pressure and temperature sensors are also placed which help record these parameters in real time. Such a system enables the choice of depth, injection rate, loading and unloading sequence controlled from the surface. Realtime optimization is possible as pressure/temperature data helps draw accurate gradient curves. This system makes gas lift optimization possible in dual gas lift wells. It has been estimated that this technology delivers a production increase approaching 20% for single completion wells, and exceeding 40% for dual-string gas lifted wells. Recognizing this opportunity, a business case and implementation plan were developed to pilot a dual-string digitally controlled gas lift optimization system. This paper will describe, the screening phase, business case preparation, risk assessment and validation process, leading to this 1st worldwide implementation of a fully optimized dual completion gas lifted well. Implementation plan of novel digital gas lift production optimization technology in an onshore dual completion well. The completely original approach increases safety, efficiency, operability and surveillance.
{"title":"First Digital Intelligent Artificial Lift Production Optimization Technology in UAE Dual-String Gas Lift Well - Business Case and Implementation Plan","authors":"Ahmed Alshmakhy, Khadija Al Daghar, Sameer Punnapala, S. Alshehhi, A. Amara, G. Makin, Stephen Faux","doi":"10.2118/196146-ms","DOIUrl":"https://doi.org/10.2118/196146-ms","url":null,"abstract":"\u0000 \u0000 \u0000 Majority of the world's gas lifted wells are under-optimized owing to changing reservoir conditions and fluid composition. The gas lift valve (GLV) calibration is required with changing conditions. Apart from that, an allowance needs to be kept so that the valve change remains valid for longer time. Compounding this, when adjusting gas lift parameters, it was not easy for the gas lift operator to make data-driven decisions to assure continuous maximized production. These challenges are further amplified with dual completion strings: fluctuating casing pressure; unpredictable temperatures due to the proximity of the two strings; and inability to individually control the injection rates to each string. String dedicated to the formation with lower productivity and reservoir pressure tends to \"rob\" gas from other string. Operating philosophy in such cases end up producing from one string. Production optimization in such cases requires frequent intervention with attendant costs and risks thus presents an opportunity to re-imagine gas lift well design.\u0000 \u0000 \u0000 \u0000 ADNOC in collaboration with Silverwell developed a Digital Intelligent Artificial Lift (DIAL) system, which consists of multiple port mandrels to be placed at GLV depths. These mandrels are connetced to the surface operating system with a single electrical cable. The ports can be selectively opened or closed by sending an electric signal from the surface unit. In addition, pressure and temperature sensors are also placed which help record these parameters in real time. Such a system enables the choice of depth, injection rate, loading and unloading sequence controlled from the surface. Realtime optimization is possible as pressure/temperature data helps draw accurate gradient curves. This system makes gas lift optimization possible in dual gas lift wells.\u0000 \u0000 \u0000 \u0000 It has been estimated that this technology delivers a production increase approaching 20% for single completion wells, and exceeding 40% for dual-string gas lifted wells. Recognizing this opportunity, a business case and implementation plan were developed to pilot a dual-string digitally controlled gas lift optimization system.\u0000 \u0000 \u0000 \u0000 This paper will describe, the screening phase, business case preparation, risk assessment and validation process, leading to this 1st worldwide implementation of a fully optimized dual completion gas lifted well. Implementation plan of novel digital gas lift production optimization technology in an onshore dual completion well. The completely original approach increases safety, efficiency, operability and surveillance.\u0000","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82625215","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}
We provide experimental evidence of wettability alteration using seawater salinity brine of an oil-wet system composed of a three-dimensional carbonate micromodel, crude oil, and connate-water brine salinity. We designed this procedure as a first step for evaluation of using seawater as an Improved Oil Recovery (IOR) agent. Our innovative design combines two main experimental best practices: micromodels, for repeatable experiments and X-ray computed tomography (CT) as a non-invasive technique for monitoring in situ fluid distribution. Both practices merge into a new three-dimensional micromodel set-up that uses only reservoir species (no high x-ray contrast chemicals). Wettability alteration plays a key role to improve oil recovery from matrix blocks surrounded by water-invaded fractures in carbonate reservoir rocks. We designed a simple and replicable experimental apparatus and procedure to quantify contact angle distributions inside of porous media with a controlled level of heterogeneity in roughness and mineralogy. This experiment consists of visualizing the in-situ contact angle distribution of the aqueous phase inside a three-dimensional carbonate micromodel. Using Micro Computerized Tomography (MicroCT), we obtained three-dimensional images of fluid distribution with a voxel size of 3.8 microns. We successfully studied the wettability state after connate water displacement and we also altered wettability of the carbonate porous medium from more oil wet to less water wet conditions. The water contact angle of the ganglia showed a 70% reduction in contact angle from an oil-wet to a water-wet system using an approximate seawater salinity and a 63% reduction in contact angle in the case of a full synthetic seawater. The initial average contact angles were 140° and 142° for the two solutions, respectively. After EOR seawater flooding, the average contact angle declined to 44° and 51°, respectively.
{"title":"Wettability Alteration of Carbonates with Seawater and Higher Salinity Brines Explored Using a 3D Micromodel","authors":"Grecia Ro","doi":"10.2118/199772-stu","DOIUrl":"https://doi.org/10.2118/199772-stu","url":null,"abstract":"\u0000 We provide experimental evidence of wettability alteration using seawater salinity brine of an oil-wet system composed of a three-dimensional carbonate micromodel, crude oil, and connate-water brine salinity. We designed this procedure as a first step for evaluation of using seawater as an Improved Oil Recovery (IOR) agent. Our innovative design combines two main experimental best practices: micromodels, for repeatable experiments and X-ray computed tomography (CT) as a non-invasive technique for monitoring in situ fluid distribution. Both practices merge into a new three-dimensional micromodel set-up that uses only reservoir species (no high x-ray contrast chemicals).\u0000 Wettability alteration plays a key role to improve oil recovery from matrix blocks surrounded by water-invaded fractures in carbonate reservoir rocks. We designed a simple and replicable experimental apparatus and procedure to quantify contact angle distributions inside of porous media with a controlled level of heterogeneity in roughness and mineralogy. This experiment consists of visualizing the in-situ contact angle distribution of the aqueous phase inside a three-dimensional carbonate micromodel. Using Micro Computerized Tomography (MicroCT), we obtained three-dimensional images of fluid distribution with a voxel size of 3.8 microns.\u0000 We successfully studied the wettability state after connate water displacement and we also altered wettability of the carbonate porous medium from more oil wet to less water wet conditions. The water contact angle of the ganglia showed a 70% reduction in contact angle from an oil-wet to a water-wet system using an approximate seawater salinity and a 63% reduction in contact angle in the case of a full synthetic seawater. The initial average contact angles were 140° and 142° for the two solutions, respectively. After EOR seawater flooding, the average contact angle declined to 44° and 51°, respectively.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83747218","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}
W. Xu, K. Chen, L. Fang, Yingchun Zhang, Z. Jing, Jun Liu, Jingyun Zou
The lacustrine delta sandbody deposited in the north of Albert Basin is unconsolidated due to the shallow burial depth, which leads to an ultra-high permeability (up to 20 D) with large variation and poor diagenesis. Log derived permeability differs greatly with DST results. Thus, permeability simulation is challenging in 3D geomodeling. A hierarchical geomodeling approach is presented to bridge the gap among the ultra-high permeability log, model and DST results. The ultimate permeability model successfully matched the logging data and DST results into the geological model. Based on the study of sedimentary microfacies, the new method identifies different discrete rocktypes (DRT) according to the analyis of core, thin section and conventional and special core analysis (e.g., capillary pressure). In this procedure, pore throat radius, flow zone index (FZI) and other parameters are taken into account to identify the DRT. Then, hierarchical modeling approach is utilized in the geomodeling. Firstly, the sedimentary microfacies model is established within the stratigraphic framework. Secondly, the spatial distribution model of DRT is established under the control of sedimentary microfacies. Thirdly, the permeability distribution is simulated according to the different pore-permeability relation functions derived from each DRT. Finally, the permeability model is compared with the logging and testing results. Winland equation was improved based on the capillary pressure (Pc) data of special core analysis. It is found that the highest correlation between pore throat radius and reservoir properties was reached when mercury injection was 35%. The corresponding formula of R35 is selected to calculate the radius of reservoir pore throat. Reservoirs are divided into four discrete rock types according to parameters such as pore throat radius and flow zone index. Each rock type has its respective lithology, thin section feature and pore-permeability relationship. The ultra-high permeability obtained by DST test reaches up to 20 D, which belongs to the first class (DRT1) quality reservoir. It is located in the center of the delta channel with high degree of sorting and roundness. DRT4 is mainly located in the bank of the channels. It has a much higher shale content and the permeability is generally less than 50 mD. Through three-dimensional geological model, sedimentary facies, rock types and pore-permeability model are coupled hierarchically. Different pore-permeability relationships are given to different DRTs. After reconstructing the permeability model, the simulation results are highly matched with the log and DST test results. This hierarchical geomodeling approach can effectively solve the simulation problem in the ultra-high permeability reservoir. It realizes a quantitative characterization for the complex reservoir heterogeneity. The method presented can be applied to clastic reservoir. It also plays a significant positive role in carbonate reser
{"title":"Hierarchical Geomodeling Approach for Ultra High Permeability Reservoir","authors":"W. Xu, K. Chen, L. Fang, Yingchun Zhang, Z. Jing, Jun Liu, Jingyun Zou","doi":"10.2118/195861-ms","DOIUrl":"https://doi.org/10.2118/195861-ms","url":null,"abstract":"\u0000 The lacustrine delta sandbody deposited in the north of Albert Basin is unconsolidated due to the shallow burial depth, which leads to an ultra-high permeability (up to 20 D) with large variation and poor diagenesis. Log derived permeability differs greatly with DST results. Thus, permeability simulation is challenging in 3D geomodeling. A hierarchical geomodeling approach is presented to bridge the gap among the ultra-high permeability log, model and DST results. The ultimate permeability model successfully matched the logging data and DST results into the geological model.\u0000 Based on the study of sedimentary microfacies, the new method identifies different discrete rocktypes (DRT) according to the analyis of core, thin section and conventional and special core analysis (e.g., capillary pressure). In this procedure, pore throat radius, flow zone index (FZI) and other parameters are taken into account to identify the DRT. Then, hierarchical modeling approach is utilized in the geomodeling. Firstly, the sedimentary microfacies model is established within the stratigraphic framework. Secondly, the spatial distribution model of DRT is established under the control of sedimentary microfacies. Thirdly, the permeability distribution is simulated according to the different pore-permeability relation functions derived from each DRT. Finally, the permeability model is compared with the logging and testing results.\u0000 Winland equation was improved based on the capillary pressure (Pc) data of special core analysis. It is found that the highest correlation between pore throat radius and reservoir properties was reached when mercury injection was 35%. The corresponding formula of R35 is selected to calculate the radius of reservoir pore throat. Reservoirs are divided into four discrete rock types according to parameters such as pore throat radius and flow zone index. Each rock type has its respective lithology, thin section feature and pore-permeability relationship. The ultra-high permeability obtained by DST test reaches up to 20 D, which belongs to the first class (DRT1) quality reservoir. It is located in the center of the delta channel with high degree of sorting and roundness. DRT4 is mainly located in the bank of the channels. It has a much higher shale content and the permeability is generally less than 50 mD. Through three-dimensional geological model, sedimentary facies, rock types and pore-permeability model are coupled hierarchically. Different pore-permeability relationships are given to different DRTs. After reconstructing the permeability model, the simulation results are highly matched with the log and DST test results.\u0000 This hierarchical geomodeling approach can effectively solve the simulation problem in the ultra-high permeability reservoir. It realizes a quantitative characterization for the complex reservoir heterogeneity. The method presented can be applied to clastic reservoir. It also plays a significant positive role in carbonate reser","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75626567","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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