Augustine James Effiong, Joseph O. Etim, Anietie Ndarake Okon
An artificial neural network (ANN) was developed to predict skin, a formation damage parameter in oil and gas drilling, well completion and production operations. Four performance metrics: goodness of fit (R2), mean square error (MSE), root mean square error (RMSE), average absolute percentage relative error (AAPRE), was used to check the performance of the developed model. The results obtained indicate that the model had an overall MSE of 355.343, RMSE of 18.850, AAPRE of 4.090 and an R2 of 0.9978. All the predictions agreed with the measured result. The generalization capacity of the developed ANN model was assessed using 500 randomly generated datasets that were not part of the model training process. The results obtained indicate that the developed model predicted 97% of these new datasets with an MSE of 375.021, RMSE of 19.370, AAPRE of 6.090 and R2 of 0.9731, while Standing (1970) equation resulted in R2of −0.807, MSE of 9.34×1016, AAPRE of 3.10×106 and RMSE of 4.10×105. The relative importance analysis of the model input parameters showed that the flow rates (q), permeability (k), porosity (φ) and pressure drop (Δp) had a significant impact on the skin (S) values estimated from the downhole. Thus, the developed model if embedded in a downhole (sensing) tool that capture these basic or required reservoir parameters: pressure, flowrate, permeability, viscosity, and thickness, would eliminate the diagnostic approach of estimating skin factor in the petroleum industry.
{"title":"Artificial Intelligence Model for Predicting Formation Damage in Oil and Gas Wells","authors":"Augustine James Effiong, Joseph O. Etim, Anietie Ndarake Okon","doi":"10.2118/207129-ms","DOIUrl":"https://doi.org/10.2118/207129-ms","url":null,"abstract":"\u0000 An artificial neural network (ANN) was developed to predict skin, a formation damage parameter in oil and gas drilling, well completion and production operations. Four performance metrics: goodness of fit (R2), mean square error (MSE), root mean square error (RMSE), average absolute percentage relative error (AAPRE), was used to check the performance of the developed model. The results obtained indicate that the model had an overall MSE of 355.343, RMSE of 18.850, AAPRE of 4.090 and an R2 of 0.9978. All the predictions agreed with the measured result. The generalization capacity of the developed ANN model was assessed using 500 randomly generated datasets that were not part of the model training process. The results obtained indicate that the developed model predicted 97% of these new datasets with an MSE of 375.021, RMSE of 19.370, AAPRE of 6.090 and R2 of 0.9731, while Standing (1970) equation resulted in R2of −0.807, MSE of 9.34×1016, AAPRE of 3.10×106 and RMSE of 4.10×105. The relative importance analysis of the model input parameters showed that the flow rates (q), permeability (k), porosity (φ) and pressure drop (Δp) had a significant impact on the skin (S) values estimated from the downhole. Thus, the developed model if embedded in a downhole (sensing) tool that capture these basic or required reservoir parameters: pressure, flowrate, permeability, viscosity, and thickness, would eliminate the diagnostic approach of estimating skin factor in the petroleum industry.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86517583","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}
N. Ohia, S. Ekwueme, G. Achumba, Ndubuisi Okechukwu Okereke, Ifeanyi Valerian Nwankwo, Onyebuchi Ivan Nnwanwe
Excessive torque and drag, buckling and shear forces on downhole strings and tubulars are often encountered in the drilling of longer reach or deviational wells. Buckling of drillstring and BHA occurs in drillstring mainly due to high compressive forces. A point may be reached where these compressive forces rise and exceed the critical buckling loads leading to buckling of the drillstring/BHA or tubulars. This study focuses on the evaluation of the effect of tool-joint on the buckling of drillstrings for highly deviated wells. Tool-joint in pipes changes the pipes geometry in the wellbore thus affecting its hydraulics, orientation and stress distribution. A notable error will arise when straight pipe (with uniform outside diameter (OD) models are used to model pipes with end couplings and connections (such as tool joints). These errors may impact critical buckling loads, buckling initiation points, and post-buckling analysis of the pipe or BHA, thus affecting the success of drilling and completion operations. Torque and drag simulation and analysis was carried out for drillstring and BHA components in 9 5/8 in casing and 8.5 in open-hole sections to determine buckling loads. Two cases were considered; case 1 investigated the modeling and definition of buckling conditions for single straight body drillstrings and case 2 evaluated the buckling conditions for tool-jointed pipes. The result shows that buckling in tool-jointed pipes follows similar trend to that of straight body pipes with sinusoidal or lateral buckling being initiated first, and gradually progresses to helical buckling on increased axial force transfer. Furthermore, from the comparison of the results from two cases considered, it was observed that the presence tool-joint in the pipes led to a critical buckling load of 5.8% for sinusoidal buckling modes. The paper suggests that higher compressive force is needed to buckle the tool-jointed ends of the drillstring than the straight ends.
{"title":"Analysis of Critical Buckling Loads For Tool-Jointed Drillstrings in Deviated Wellbores","authors":"N. Ohia, S. Ekwueme, G. Achumba, Ndubuisi Okechukwu Okereke, Ifeanyi Valerian Nwankwo, Onyebuchi Ivan Nnwanwe","doi":"10.2118/207202-ms","DOIUrl":"https://doi.org/10.2118/207202-ms","url":null,"abstract":"Excessive torque and drag, buckling and shear forces on downhole strings and tubulars are often encountered in the drilling of longer reach or deviational wells. Buckling of drillstring and BHA occurs in drillstring mainly due to high compressive forces. A point may be reached where these compressive forces rise and exceed the critical buckling loads leading to buckling of the drillstring/BHA or tubulars. This study focuses on the evaluation of the effect of tool-joint on the buckling of drillstrings for highly deviated wells. Tool-joint in pipes changes the pipes geometry in the wellbore thus affecting its hydraulics, orientation and stress distribution. A notable error will arise when straight pipe (with uniform outside diameter (OD) models are used to model pipes with end couplings and connections (such as tool joints). These errors may impact critical buckling loads, buckling initiation points, and post-buckling analysis of the pipe or BHA, thus affecting the success of drilling and completion operations. Torque and drag simulation and analysis was carried out for drillstring and BHA components in 9 5/8 in casing and 8.5 in open-hole sections to determine buckling loads. Two cases were considered; case 1 investigated the modeling and definition of buckling conditions for single straight body drillstrings and case 2 evaluated the buckling conditions for tool-jointed pipes. The result shows that buckling in tool-jointed pipes follows similar trend to that of straight body pipes with sinusoidal or lateral buckling being initiated first, and gradually progresses to helical buckling on increased axial force transfer. Furthermore, from the comparison of the results from two cases considered, it was observed that the presence tool-joint in the pipes led to a critical buckling load of 5.8% for sinusoidal buckling modes. The paper suggests that higher compressive force is needed to buckle the tool-jointed ends of the drillstring than the straight ends.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74813021","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}
Victoria Kamnetochi Ikpeze, J. Owolabi, I. I. Olateju, A. Giwa
This work has been carried out to model and simulate a typical acid gas absorption process using Aspen HYSYS process simulator. The chemical components involved in the process development were water, methane, ethane, propane, higher alkanes, carbon dioxide, hydrogen sulphide, nitrogen and amines: monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA) and methyldiethanolamine (MDEA). The fluid package selected for the simulation before entering the simulation environment was Acid Gas – Chemical Solvents. In the simulation environment, the model was developed by picking an absorber from the Model Palette, placing it and assigning the input and the output streams involved before inputting the parameters required for model convergence. The carbon dioxide-rich feed gas was made to enter the absorber at the bottom inlet stream while the lean amine stream entered at the top inlet and showered down on the uprising gas thereby trapping the carbon dioxide molecules within the gas. The top product from the absorber was the treated gas while the amine solution and the trapped carbon dioxide left the absorber as the bottom product. Different simulations were run to investigate the performance of the amines under the same operating conditions. It was discovered that, of all the four amine solvents considered in this work for the removal of carbon dioxide by chemical absorption, MEA had the highest efficiency but would require more dehydration because it had the highest water content. DEA was also found to scrub the carbon dioxide down to acceptable levels. However, TEA and MDEA barely scrubbed any carbon dioxide under these conditions, as their carbon dioxide compositions were found to be unacceptable. The analyses of the results obtained from the simulations indicated that Aspen HYSYS can be used to study the process of acid gas absorption successfully.
{"title":"Modelling and Simulation of Acid Gas Absorption from Natural Gas by Amine Solution Using Aspen HYSYS","authors":"Victoria Kamnetochi Ikpeze, J. Owolabi, I. I. Olateju, A. Giwa","doi":"10.2118/207183-ms","DOIUrl":"https://doi.org/10.2118/207183-ms","url":null,"abstract":"\u0000 This work has been carried out to model and simulate a typical acid gas absorption process using Aspen HYSYS process simulator. The chemical components involved in the process development were water, methane, ethane, propane, higher alkanes, carbon dioxide, hydrogen sulphide, nitrogen and amines: monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA) and methyldiethanolamine (MDEA). The fluid package selected for the simulation before entering the simulation environment was Acid Gas – Chemical Solvents. In the simulation environment, the model was developed by picking an absorber from the Model Palette, placing it and assigning the input and the output streams involved before inputting the parameters required for model convergence. The carbon dioxide-rich feed gas was made to enter the absorber at the bottom inlet stream while the lean amine stream entered at the top inlet and showered down on the uprising gas thereby trapping the carbon dioxide molecules within the gas. The top product from the absorber was the treated gas while the amine solution and the trapped carbon dioxide left the absorber as the bottom product. Different simulations were run to investigate the performance of the amines under the same operating conditions. It was discovered that, of all the four amine solvents considered in this work for the removal of carbon dioxide by chemical absorption, MEA had the highest efficiency but would require more dehydration because it had the highest water content. DEA was also found to scrub the carbon dioxide down to acceptable levels. However, TEA and MDEA barely scrubbed any carbon dioxide under these conditions, as their carbon dioxide compositions were found to be unacceptable. The analyses of the results obtained from the simulations indicated that Aspen HYSYS can be used to study the process of acid gas absorption successfully.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83070984","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}
Udeme John, Ibi-Ada Itotoi, A. Isah, Anita Odiete, Erome Utunedi, Musa Mohamma, Martins Ikhuehi
The largest component of operating costs in most matured assets utilizing 3rd party evacuation infrastructure is crude handling charges. In mature fields with significant water production, water volumes could easily account for over half of crude handling costs. Produced water re-injection for disposal has become a popular strategy for optimizing liquid handling cost as well as supporting environmental responsibility. Injectivity for water disposal wells have been demonstrated to decline with time, the most common factor being permeability reduction arising mostly from fines migration, suspended and dissolved solids in injected water, microbial activities, oil in water and cation concentrations, etc. Thus, Injection wells typically require intermittent stimulation to restore or improve injectivity. Fracturing has been demonstrated to prolong injectivity. However, sustainability is greatly affected by ability to keep fractures open after shut-ins and limited by environmental regulations. Understanding the key mechanisms that lead to injectivity decline will help optimize produced water reinjection systems, enable proactive intervention planning, thus improve injectivity and well availability. In this work we present the development of an injectivity modelling and simulation tool called IDS based on relatively recent injectivity models. Testing and validation of the tool using standard data and an active onshore Niger-Delta Produced Water Reinjection Project as a case study are presented. An outstanding feature of this simulator is its ability to estimate missing parameters or those whose values are not known to high fidelity via history matching. The resulting nonlinear regression problem is solved using a trust-region reflective approach. Decline mechanism regression parameters were similar for a well that had multiple injection periods. Transition time from deep bed to external cake is very sensitive to Total Suspended Solids (TSS) in injected water. Injectivity half-life could increase by as much as 100% for about a 100% drop in mean TSS concentration. The IDS tool was used to predict the injectivity half-life of Well A in the water disposal project.
{"title":"Development of Injectivity Decline Modelling Tool: A Case Study of Onshore Niger Delta Produced Water Re-Injection Project","authors":"Udeme John, Ibi-Ada Itotoi, A. Isah, Anita Odiete, Erome Utunedi, Musa Mohamma, Martins Ikhuehi","doi":"10.2118/207087-ms","DOIUrl":"https://doi.org/10.2118/207087-ms","url":null,"abstract":"\u0000 The largest component of operating costs in most matured assets utilizing 3rd party evacuation infrastructure is crude handling charges. In mature fields with significant water production, water volumes could easily account for over half of crude handling costs. Produced water re-injection for disposal has become a popular strategy for optimizing liquid handling cost as well as supporting environmental responsibility.\u0000 Injectivity for water disposal wells have been demonstrated to decline with time, the most common factor being permeability reduction arising mostly from fines migration, suspended and dissolved solids in injected water, microbial activities, oil in water and cation concentrations, etc. Thus, Injection wells typically require intermittent stimulation to restore or improve injectivity. Fracturing has been demonstrated to prolong injectivity. However, sustainability is greatly affected by ability to keep fractures open after shut-ins and limited by environmental regulations. Understanding the key mechanisms that lead to injectivity decline will help optimize produced water reinjection systems, enable proactive intervention planning, thus improve injectivity and well availability.\u0000 In this work we present the development of an injectivity modelling and simulation tool called IDS based on relatively recent injectivity models. Testing and validation of the tool using standard data and an active onshore Niger-Delta Produced Water Reinjection Project as a case study are presented.\u0000 An outstanding feature of this simulator is its ability to estimate missing parameters or those whose values are not known to high fidelity via history matching. The resulting nonlinear regression problem is solved using a trust-region reflective approach.\u0000 Decline mechanism regression parameters were similar for a well that had multiple injection periods. Transition time from deep bed to external cake is very sensitive to Total Suspended Solids (TSS) in injected water. Injectivity half-life could increase by as much as 100% for about a 100% drop in mean TSS concentration. The IDS tool was used to predict the injectivity half-life of Well A in the water disposal project.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76019812","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}
Saturation logging tool is one key tool that has been successfully used in the Oil and Gas Industry. As important as the tool is, it should not be mistaken for a decision tool, rather it is a tool that aids decision making. Because the tool aids decision making, the decision process must be undertaken by interdisciplinary team of Engineers with historical knowledge of the tool and the performance trend of the candidate well and reservoir. No expertise is superior to historical data of well and reservoir performance because the duo follows physics and any deviation from it is attributable to a misnomer. The decision to re-enter a well for re-perforation or workover must be supported by historical production and reasonable science which here means that trends are sustained on continuous physics and not abrupt pulses. Any interpretation arising from saturation logging tools without subjecting same to reasonable science could result in wrong action. This paper is providing a methodology to enhance thorough screening of candidates for saturation logging operations. First is to determine if the candidate well is multilevel and historical production above critical gas rate before shut-in to screen-out liquid loading consideration. If any level is plugged below any producing level, investigate for micro-annuli leakage. All historical liquid loading wells should be flowed at rate above critical rate and logged at flow condition. Static condition logging is only good for non-liquid loading wells. The use of any tool and its interpretation must be subjective and there comes the clash between the experienced Sales Engineer and the Production/Reservoir Engineer with the historical evidence. A simple historical trending and analysis results of API gravity and BS&W were used in the failed plug case-study. Further successful investigation was done and the results of the well performance afterwards negated the interpretation arising from the saturation tool which saw the reservoir sand flushed. The lesson learnt from the well logging and interpretation shows that when a well is under any form of liquid loading, interpretation must be subjective with reasonable science and historical production trend is critical. It is recommended that when a well is under historical liquid loading rate, until the rate above the critical rate is determined, no logging should be done and when done, logging should be at flow condition and the interpretation subject to reasonable system physics.
{"title":"The Limitation of Reservoir Saturation Logging Tool in a Case of a Deeper Reservoir Flow into a Shallower Reservoir Within the Same Wellbore","authors":"P. M. Ekeregbe","doi":"10.2118/207115-ms","DOIUrl":"https://doi.org/10.2118/207115-ms","url":null,"abstract":"\u0000 Saturation logging tool is one key tool that has been successfully used in the Oil and Gas Industry. As important as the tool is, it should not be mistaken for a decision tool, rather it is a tool that aids decision making. Because the tool aids decision making, the decision process must be undertaken by interdisciplinary team of Engineers with historical knowledge of the tool and the performance trend of the candidate well and reservoir. No expertise is superior to historical data of well and reservoir performance because the duo follows physics and any deviation from it is attributable to a misnomer.\u0000 The decision to re-enter a well for re-perforation or workover must be supported by historical production and reasonable science which here means that trends are sustained on continuous physics and not abrupt pulses. Any interpretation arising from saturation logging tools without subjecting same to reasonable science could result in wrong action. This paper is providing a methodology to enhance thorough screening of candidates for saturation logging operations. First is to determine if the candidate well is multilevel and historical production above critical gas rate before shut-in to screen-out liquid loading consideration. If any level is plugged below any producing level, investigate for micro-annuli leakage. All historical liquid loading wells should be flowed at rate above critical rate and logged at flow condition. Static condition logging is only good for non-liquid loading wells.\u0000 The use of any tool and its interpretation must be subjective and there comes the clash between the experienced Sales Engineer and the Production/Reservoir Engineer with the historical evidence. A simple historical trending and analysis results of API gravity and BS&W were used in the failed plug case-study. Further successful investigation was done and the results of the well performance afterwards negated the interpretation arising from the saturation tool which saw the reservoir sand flushed.\u0000 The lesson learnt from the well logging and interpretation shows that when a well is under any form of liquid loading, interpretation must be subjective with reasonable science and historical production trend is critical. It is recommended that when a well is under historical liquid loading rate, until the rate above the critical rate is determined, no logging should be done and when done, logging should be at flow condition and the interpretation subject to reasonable system physics.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72793258","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}
Optimizing decision and design variables for Chemical EOR is imperative for sensitivity and uncertainty analysis. However, these processes involve multiple reservoir simulation runs which increase computational cost and time. Surrogate models are capable of overcoming this impediment as they are capable of mimicking the capabilities of full field three-dimensional reservoir simulation models in detail and complexity. Artificial Neural Networks (ANN) and regression-based Design of Experiments (DoE) are common methods for surrogate modelling. In this study, a comparative analysis of data-driven surrogate model performance on Recovery Factor (RF) for Surfactant-Polymer flooding is investigated with seven input variables including Kv/Kh ratio, polymer concentration in polymer drive, surfactant slug size, surfactant concentration in surfactant slug, polymer concentration in surfactant slug, polymer drive size and salinity of polymer drive. Eleven Machine learning models including Multiple Linear Regression (MLR), Ridge and Lasso regression; Support Vector Regression (SVR), ANN as well as Classification and Regression Tree (CART) based algorithms including Decision Trees, Random Forest, eXtreme Gradient Boosting (XGBoost), Gradient Boosting and Extremely Randomized Trees (ERT), are applied on a dataset consisting of 202 datapoints. The results obtained indicate high model performance and accuracy for SVR, ANN and CART based ensemble techniques like Extremely Randomized Trees, Gradient Boost and XGBoost regression, with high R2 values and lowest Mean Squared Error (MSE) values for the training and test dataset. Unlike other studies on Chemical EOR surrogate modelling where sensitivity was analyzed with statistical DoE, we rank the input features using Decision Tree-based algorithms while model interpretability is achieved with Shapely Values. Results from feature ranking indicate that surfactant concentration, and slug size are the most influential parameters on the RF. Other important factors, though with less influence, are the polymer concentration in surfactant slug, polymer concentration in polymer drive and polymer drive size. The salinity of the polymer drive and the Kv/Kh ratio both have a negative effect on the RF, with a corresponding least level of significance.
{"title":"Surrogate-Based Analysis of Chemical Enhanced Oil Recovery – A Comparative Analysis of Machine Learning Model Performance","authors":"Akpevwe Kelvin Idogun, Ruth Oyanu Ujah, L. James","doi":"10.2118/208452-ms","DOIUrl":"https://doi.org/10.2118/208452-ms","url":null,"abstract":"\u0000 Optimizing decision and design variables for Chemical EOR is imperative for sensitivity and uncertainty analysis. However, these processes involve multiple reservoir simulation runs which increase computational cost and time. Surrogate models are capable of overcoming this impediment as they are capable of mimicking the capabilities of full field three-dimensional reservoir simulation models in detail and complexity. Artificial Neural Networks (ANN) and regression-based Design of Experiments (DoE) are common methods for surrogate modelling. In this study, a comparative analysis of data-driven surrogate model performance on Recovery Factor (RF) for Surfactant-Polymer flooding is investigated with seven input variables including Kv/Kh ratio, polymer concentration in polymer drive, surfactant slug size, surfactant concentration in surfactant slug, polymer concentration in surfactant slug, polymer drive size and salinity of polymer drive. Eleven Machine learning models including Multiple Linear Regression (MLR), Ridge and Lasso regression; Support Vector Regression (SVR), ANN as well as Classification and Regression Tree (CART) based algorithms including Decision Trees, Random Forest, eXtreme Gradient Boosting (XGBoost), Gradient Boosting and Extremely Randomized Trees (ERT), are applied on a dataset consisting of 202 datapoints. The results obtained indicate high model performance and accuracy for SVR, ANN and CART based ensemble techniques like Extremely Randomized Trees, Gradient Boost and XGBoost regression, with high R2 values and lowest Mean Squared Error (MSE) values for the training and test dataset. Unlike other studies on Chemical EOR surrogate modelling where sensitivity was analyzed with statistical DoE, we rank the input features using Decision Tree-based algorithms while model interpretability is achieved with Shapely Values. Results from feature ranking indicate that surfactant concentration, and slug size are the most influential parameters on the RF. Other important factors, though with less influence, are the polymer concentration in surfactant slug, polymer concentration in polymer drive and polymer drive size. The salinity of the polymer drive and the Kv/Kh ratio both have a negative effect on the RF, with a corresponding least level of significance.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72830677","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}
To maximize production from mature fields, it is essential to identify candidate's wells that are not producing up to their potential. Performing periodic interventions or workovers in wells is an established approach for arresting production decline and maximizing production from the fields. However, for mature fields with large well counts, the process of determining the best candidates for well interventions can be complicated and tedious. This can result in less-than-optimal outcomes. Advanced data analytics modeling offers quick and easy access to important information. The main objective of this study is to identify potential candidate wells for workover operation ahead of time so that we can fix them before they become problem. This was achieved via principal component analysis with the aid of XLSTAT in Excel. In this study, we developed a model based on PCA to quickly identify and rank the workover candidate's wells. The dataset used in this project comprises of 66 oil wells and were obtained from a field operating in the Niger Delta. The first step involved data gathering and validation and uploading into XLSTAT software. Data preprocessing procedures were conducted to condition the dataset so as to give optimum performance during model development. A model was built to identify potential wells for workover operation. The results obtained here showed that the wells are separated to areas designated as (A to E). Wells found in area A indicated that they are potential candidates for workover operation. Wells found in area B showed that they are not under immediate danger, but attention would be needed to monitor and prevent increasing water and gas rates in the future. Wells found in area C indicated that they required immediate attention to prevent further decline in oil production. Likewise, wells found in Area D indicated that they also required immediate attention to prevent further decline in oil production. Finally, Wells found in Area E showed that they have highest oil production, lowest water production and moderate gas production, indicating normal condition with no immediate workover operation required. With advanced data analytics modeling, reservoir engineers or geoscientists will now see a bigger picture either field by field or reservoir by reservoir and quicky identify potential candidate wells for workover operation ahead of time before they become a problem. Hence, the results of the analysis can help us to better target wells that are potential candidates for high water cut, high WOR, High gas rates and low oil rates.
{"title":"Identification of Potential Candidate's Wells for Workover","authors":"Edet Ita Okon, D. Appah","doi":"10.2118/208246-ms","DOIUrl":"https://doi.org/10.2118/208246-ms","url":null,"abstract":"\u0000 To maximize production from mature fields, it is essential to identify candidate's wells that are not producing up to their potential. Performing periodic interventions or workovers in wells is an established approach for arresting production decline and maximizing production from the fields. However, for mature fields with large well counts, the process of determining the best candidates for well interventions can be complicated and tedious. This can result in less-than-optimal outcomes. Advanced data analytics modeling offers quick and easy access to important information. The main objective of this study is to identify potential candidate wells for workover operation ahead of time so that we can fix them before they become problem. This was achieved via principal component analysis with the aid of XLSTAT in Excel. In this study, we developed a model based on PCA to quickly identify and rank the workover candidate's wells. The dataset used in this project comprises of 66 oil wells and were obtained from a field operating in the Niger Delta. The first step involved data gathering and validation and uploading into XLSTAT software. Data preprocessing procedures were conducted to condition the dataset so as to give optimum performance during model development. A model was built to identify potential wells for workover operation. The results obtained here showed that the wells are separated to areas designated as (A to E). Wells found in area A indicated that they are potential candidates for workover operation. Wells found in area B showed that they are not under immediate danger, but attention would be needed to monitor and prevent increasing water and gas rates in the future. Wells found in area C indicated that they required immediate attention to prevent further decline in oil production. Likewise, wells found in Area D indicated that they also required immediate attention to prevent further decline in oil production. Finally, Wells found in Area E showed that they have highest oil production, lowest water production and moderate gas production, indicating normal condition with no immediate workover operation required. With advanced data analytics modeling, reservoir engineers or geoscientists will now see a bigger picture either field by field or reservoir by reservoir and quicky identify potential candidate wells for workover operation ahead of time before they become a problem. Hence, the results of the analysis can help us to better target wells that are potential candidates for high water cut, high WOR, High gas rates and low oil rates.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89660114","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}
E. Ayodele, David Ekuma, I. Okafor, Innocent E Nweze
Drilling fluid are complex fluids consisting of several additives. These additives are added to enhance and control the rheological properties (such as viscosity, gel strength and yield point) of the mud. These properties are controlled for effective drilling of a well. This research work is focused on determining the rheological behavior of drilling mud using industry-based polymer and Irvingia Gabonensis (ogbono) as viscosifiers. Water based muds were formulated from the aforementioned locally sourced viscosifier and that of the conventional used viscosifier (Carboxylmetyl cellulose, CMC). Laboratory tests were carried out on the different muds formulated and their rheological properties (such as yield stress, shear stress, plastic viscosity and shear rate) are evaluated. The concentration of the viscosifiers were varied. The expected outcome of the research work aims at lowering the total drilling cost by reducing the importation of foreign polymer which promotes the development of local content in the oil and gas industry. The research compares the rheology of mud samples and the effect of varying the concentration (2g, 4g, 6g, 8g, and 10g) of both CMC and Ogbono and determining the changes in their rheological properties. The total volume of each mud sample is equivalent to 350ml which represent one barrel (42gal) in the lab. From the result, at concentration of 2g, the ogbono mud has a better rheology than the CMC mud, but at a concentration above 2g, CMC mud shows a better rheology than ogbono mud, that is, as the concentration of CMC is increased, the rheological properties of the mud increased while as the concentration of ogbono is increased the rheological properties decreased. The viscosity of the drilling fluid produced from the ogbono were lower than that of CMC, it could be used together with another local product such as cassava starch, offor or to further improve the rheology and then be a substitute to the conventional viscosifiers.
{"title":"Comparative Analysis of the Rheological Behaviour of Irvingia Gabonensis Ogbono and Foreign Polymer for Bentonite Formulated Mud.","authors":"E. Ayodele, David Ekuma, I. Okafor, Innocent E Nweze","doi":"10.2118/207112-ms","DOIUrl":"https://doi.org/10.2118/207112-ms","url":null,"abstract":"\u0000 Drilling fluid are complex fluids consisting of several additives. These additives are added to enhance and control the rheological properties (such as viscosity, gel strength and yield point) of the mud. These properties are controlled for effective drilling of a well. This research work is focused on determining the rheological behavior of drilling mud using industry-based polymer and Irvingia Gabonensis (ogbono) as viscosifiers. Water based muds were formulated from the aforementioned locally sourced viscosifier and that of the conventional used viscosifier (Carboxylmetyl cellulose, CMC). Laboratory tests were carried out on the different muds formulated and their rheological properties (such as yield stress, shear stress, plastic viscosity and shear rate) are evaluated. The concentration of the viscosifiers were varied. The expected outcome of the research work aims at lowering the total drilling cost by reducing the importation of foreign polymer which promotes the development of local content in the oil and gas industry. The research compares the rheology of mud samples and the effect of varying the concentration (2g, 4g, 6g, 8g, and 10g) of both CMC and Ogbono and determining the changes in their rheological properties. The total volume of each mud sample is equivalent to 350ml which represent one barrel (42gal) in the lab. From the result, at concentration of 2g, the ogbono mud has a better rheology than the CMC mud, but at a concentration above 2g, CMC mud shows a better rheology than ogbono mud, that is, as the concentration of CMC is increased, the rheological properties of the mud increased while as the concentration of ogbono is increased the rheological properties decreased. The viscosity of the drilling fluid produced from the ogbono were lower than that of CMC, it could be used together with another local product such as cassava starch, offor or to further improve the rheology and then be a substitute to the conventional viscosifiers.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76248629","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}
Condensate reservoirs are mostly pressure sensitive and keeping the pressure above the dew point pressure in the reservoir is critical to avoid condensate banking in the reservoir. If it occurs, production is highly inhibited and the well may ultimately quit on production under liquid loading. Fluid ratios are important in the management of condensate wells and most critical is the Gas Liquid Ratio (GLR). There is a certain GLR that below it, there will be a liquid loading in the wellbore that could quit the well. Each fluid rate goes with a GLR and the point where there is a reversal of the GLR or CGR trends may present a case of loading scenario and that is taken as the determination reference point. When a condensate well shows an improvement of water cut as the choke bean size is reduced does not necessarily signify a healthy situation and neither a one-point higher water cut with increase in choke bean size mean a water coning situation. When a liquid loading well is beaned up, there is early signs of water coning in the production data but this is just a wellbore production and the BS&W improves as the production rate is further increased. Further investigation is necessary to separate the challenge of water conning from the challenge of too low Gas rate which causes the loading of the liquids in the wellbore. That is the operating envelop to manage condensate well rates: rates too low with a possibility of a liquid loading and rates too high that depicts a case of water conning when water is close to the perforation. This band must be completely exploited to turn the production curve in the positive. This paper provides a strategy to recover a condensate well production with a challenge of liquid loading using a case study. The degree of the severity of the liquid loading can be represented using a power law model with the gradient being the level of severity of the loading. The production improvement is greater than nβ percent where n is the quadratic model number 2 and β is the product of the graphical and Lagrangian-Quadratic alpha parameters. The optimum rate can be determined using the Lagrange Multiplier optimization method to effectively extend the production life of the well.
{"title":"Determination of Optimum Rate in a Condensate Well with a Case of a Wellbore Liquid Loading","authors":"M. P. Ekeregbe","doi":"10.2118/207119-ms","DOIUrl":"https://doi.org/10.2118/207119-ms","url":null,"abstract":"\u0000 Condensate reservoirs are mostly pressure sensitive and keeping the pressure above the dew point pressure in the reservoir is critical to avoid condensate banking in the reservoir. If it occurs, production is highly inhibited and the well may ultimately quit on production under liquid loading.\u0000 Fluid ratios are important in the management of condensate wells and most critical is the Gas Liquid Ratio (GLR). There is a certain GLR that below it, there will be a liquid loading in the wellbore that could quit the well. Each fluid rate goes with a GLR and the point where there is a reversal of the GLR or CGR trends may present a case of loading scenario and that is taken as the determination reference point. When a condensate well shows an improvement of water cut as the choke bean size is reduced does not necessarily signify a healthy situation and neither a one-point higher water cut with increase in choke bean size mean a water coning situation. When a liquid loading well is beaned up, there is early signs of water coning in the production data but this is just a wellbore production and the BS&W improves as the production rate is further increased.\u0000 Further investigation is necessary to separate the challenge of water conning from the challenge of too low Gas rate which causes the loading of the liquids in the wellbore. That is the operating envelop to manage condensate well rates: rates too low with a possibility of a liquid loading and rates too high that depicts a case of water conning when water is close to the perforation. This band must be completely exploited to turn the production curve in the positive.\u0000 This paper provides a strategy to recover a condensate well production with a challenge of liquid loading using a case study. The degree of the severity of the liquid loading can be represented using a power law model with the gradient being the level of severity of the loading. The production improvement is greater than nβ percent where n is the quadratic model number 2 and β is the product of the graphical and Lagrangian-Quadratic alpha parameters. The optimum rate can be determined using the Lagrange Multiplier optimization method to effectively extend the production life of the well.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"148 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77848965","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}
Ibi-Ada Itotoi, T. Gbadamosi, Christian Ihwiwhu, Udeme John, Anita Odiete, Precious Okoro, Maduabuchi Ndubueze, Erome Utunedi, A. Awujoola, So Adesanya
Low oil price and increased environmental regulations presents a new frontier for many indigenous oil and gas companies in Nigeria. In mature fields with significant water production, produced water treatment and handling could easily account for up to a third of OPEX. Underground produced water disposal is a tested approach that has been used worldwide with mixed results. Studies have been published on the subject; however, it was observed that there were no Niger Delta case studies. This paper presents SEPLAT's subsurface approach to in-field water disposal, drawing upon geological and petroleum engineering analysis coupled with learnings from over 6 years of produced water re-injection experience. Some of the areas that will be discussed include reservoir selection/screening methodology, water quality impact on permeability, produced water disposal well selection/completion, operating philosophy, general surveillance, and basic separation requirements. Thirteen reservoirs located within 2 proximal fields were screened for suitability and ranked as possible candidates for water disposal based on 8 criteria. The best 2 were then high-graded and detailed studies carried out, spanning detailed geological characterization for reservoir quality and connectivity (including quantitative interpretation), to dynamic simulation, injection well location optimization and performance prediction (for clean water). The results of core flood tests were incorporated. It is recommended that total suspended solids should not exceed 5 mg/L, with a maximum of 5 microns particle size, under matrix injection conditions while oil content should be limited to below 30-50 ppm. Tolerance for TSS can be relaxed to 10ppm – 50ppm at fracturing conditions, depending on the reservoir parameters and process systems. The knowledge of these parameters should drive the technology selection for optimum water treatment and injection.
{"title":"Produced Water Re-Injection: An Integrated Subsurface Approach to Planning and Execution for Downhole Produced Water Disposal in the Niger Delta","authors":"Ibi-Ada Itotoi, T. Gbadamosi, Christian Ihwiwhu, Udeme John, Anita Odiete, Precious Okoro, Maduabuchi Ndubueze, Erome Utunedi, A. Awujoola, So Adesanya","doi":"10.2118/207088-ms","DOIUrl":"https://doi.org/10.2118/207088-ms","url":null,"abstract":"\u0000 Low oil price and increased environmental regulations presents a new frontier for many indigenous oil and gas companies in Nigeria. In mature fields with significant water production, produced water treatment and handling could easily account for up to a third of OPEX.\u0000 Underground produced water disposal is a tested approach that has been used worldwide with mixed results. Studies have been published on the subject; however, it was observed that there were no Niger Delta case studies. This paper presents SEPLAT's subsurface approach to in-field water disposal, drawing upon geological and petroleum engineering analysis coupled with learnings from over 6 years of produced water re-injection experience. Some of the areas that will be discussed include reservoir selection/screening methodology, water quality impact on permeability, produced water disposal well selection/completion, operating philosophy, general surveillance, and basic separation requirements.\u0000 Thirteen reservoirs located within 2 proximal fields were screened for suitability and ranked as possible candidates for water disposal based on 8 criteria. The best 2 were then high-graded and detailed studies carried out, spanning detailed geological characterization for reservoir quality and connectivity (including quantitative interpretation), to dynamic simulation, injection well location optimization and performance prediction (for clean water). The results of core flood tests were incorporated.\u0000 It is recommended that total suspended solids should not exceed 5 mg/L, with a maximum of 5 microns particle size, under matrix injection conditions while oil content should be limited to below 30-50 ppm. Tolerance for TSS can be relaxed to 10ppm – 50ppm at fracturing conditions, depending on the reservoir parameters and process systems. The knowledge of these parameters should drive the technology selection for optimum water treatment and injection.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72973143","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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