The existing decline curve analysis (DCA) equations, some with valid theoretical justifications, cannot directly react to changes in operating conditions. Thus, they all assume constant operating conditions over the flowing life of a well. This however is an obvious oversimplification. This paper begins by briefly reviewing Gilbert's equation for flowrate prediction and then the C-curve and Logistic growth model DCA theories. The above review serves to identify well key flow indicators (KFI) and performance drivers. Subsequently, a forecasting approach which involves building artificial neural network (ANN) frameworks and training them on well KFI data is presented. Using trained ANNs, production forecasts were generated for three oil wells in the Niger-Delta producing from separate reservoirs under different flow regimes. The results were compared to forecasts from traditional DCA methods and material balance simulation, as well as with future production from the wells themselves. The results indicated that trained ANNs are capable of generating better performance curves than traditional DCA, with forecasts tying closely with results of material balance simulation and measured future well production rates. The ability of trained ANNs to evaluate the effect of changes in operating conditions (i.e. FTHP, GOR and water-cut) on production profiles and reserves drainable by wells, allows for scenario forecasting which is invaluable in field development planning. This is illustrated with field cases. This paper also presents a novel approach to evaluating the optimal hyperparameter configuration (i.e. the number of layers, neuron count per layer, dropout, batch size and the learning rate) required to minimize the loss function whilst training an ANN on any given dataset. This should prove invaluable to engineers and geoscientists integrating deep learning into sub-surface analyses.
{"title":"Dynamic Production Forecasting using Artificial Neural Networks customized to historical well Key Flow Indicators","authors":"David Nnamdi, Victor O. Adelaja","doi":"10.2118/198756-MS","DOIUrl":"https://doi.org/10.2118/198756-MS","url":null,"abstract":"\u0000 The existing decline curve analysis (DCA) equations, some with valid theoretical justifications, cannot directly react to changes in operating conditions. Thus, they all assume constant operating conditions over the flowing life of a well. This however is an obvious oversimplification.\u0000 This paper begins by briefly reviewing Gilbert's equation for flowrate prediction and then the C-curve and Logistic growth model DCA theories. The above review serves to identify well key flow indicators (KFI) and performance drivers. Subsequently, a forecasting approach which involves building artificial neural network (ANN) frameworks and training them on well KFI data is presented.\u0000 Using trained ANNs, production forecasts were generated for three oil wells in the Niger-Delta producing from separate reservoirs under different flow regimes. The results were compared to forecasts from traditional DCA methods and material balance simulation, as well as with future production from the wells themselves. The results indicated that trained ANNs are capable of generating better performance curves than traditional DCA, with forecasts tying closely with results of material balance simulation and measured future well production rates. The ability of trained ANNs to evaluate the effect of changes in operating conditions (i.e. FTHP, GOR and water-cut) on production profiles and reserves drainable by wells, allows for scenario forecasting which is invaluable in field development planning. This is illustrated with field cases.\u0000 This paper also presents a novel approach to evaluating the optimal hyperparameter configuration (i.e. the number of layers, neuron count per layer, dropout, batch size and the learning rate) required to minimize the loss function whilst training an ANN on any given dataset. This should prove invaluable to engineers and geoscientists integrating deep learning into sub-surface analyses.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74664912","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}
The notion of Water Saturation is of importance in determining the hydrocarbon saturation (1-Sw) in reservoirs, calculating hydrocarbon in place, hence a vital evidence of reliable formation evaluation. Preconceptions in reserves quantification and hydrocarbon in place estimations arise once the outcome of the water saturation value is erroneous. Several models in the literature have been used for estimating water saturation and oftentimes the variance in confidence level of their results lead to substantial variance in original hydrocarbon in place volumes. Obtaining a better resolution with deeper understanding of the gaps observed in the existing approaches for estimating water saturation (Sw) values have been a major challenge in accurate calculation of hydrocarbon in place. This paper presents a non-resistivity approach for estimating water saturation using Leverett J-function and Reservoir Quality Index with dependency on fluid and facies Values. The innovative approach involves the use of Saturation Height Modelling through Leverett J- function, build facies through Magnetic Resonance Graphical-Based clustering (MRGC) option, use of Regression method and making a simple scripting using logging language (LOGLAN) program in Geolog to achieve the purpose. This current approach has been applied to Niger-Delta alternate shale-sand formation in optimisation of somewhat low recovery of the hydrocarbon reserves due to probably erroneous over estimation of Water Saturation value from Resistivity-based approach. Reliable results from current non-resistivity approach were obtained with average Water Saturation value of 25% as compared to resistivity approach presented by Juhasz with average water saturation value of 32% and non-resistivity approach presented by Brooks-Corey with average water saturation value of 26% and Leverett J- function with average water saturation values of 27% respectively.
{"title":"A Non-Resistivity Approach for Estimating Water Saturation A Case Study in Niger-Delta, Nigeria","authors":"Olabode Awuyo, A. Sunday, A. Fadairo","doi":"10.2118/198753-MS","DOIUrl":"https://doi.org/10.2118/198753-MS","url":null,"abstract":"\u0000 The notion of Water Saturation is of importance in determining the hydrocarbon saturation (1-Sw) in reservoirs, calculating hydrocarbon in place, hence a vital evidence of reliable formation evaluation. Preconceptions in reserves quantification and hydrocarbon in place estimations arise once the outcome of the water saturation value is erroneous. Several models in the literature have been used for estimating water saturation and oftentimes the variance in confidence level of their results lead to substantial variance in original hydrocarbon in place volumes. Obtaining a better resolution with deeper understanding of the gaps observed in the existing approaches for estimating water saturation (Sw) values have been a major challenge in accurate calculation of hydrocarbon in place.\u0000 This paper presents a non-resistivity approach for estimating water saturation using Leverett J-function and Reservoir Quality Index with dependency on fluid and facies Values. The innovative approach involves the use of Saturation Height Modelling through Leverett J- function, build facies through Magnetic Resonance Graphical-Based clustering (MRGC) option, use of Regression method and making a simple scripting using logging language (LOGLAN) program in Geolog to achieve the purpose. This current approach has been applied to Niger-Delta alternate shale-sand formation in optimisation of somewhat low recovery of the hydrocarbon reserves due to probably erroneous over estimation of Water Saturation value from Resistivity-based approach. Reliable results from current non-resistivity approach were obtained with average Water Saturation value of 25% as compared to resistivity approach presented by Juhasz with average water saturation value of 32% and non-resistivity approach presented by Brooks-Corey with average water saturation value of 26% and Leverett J- function with average water saturation values of 27% respectively.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84446901","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}
Blessyn Okpowo, Ebenezer Ageh, Peter Agodo, A. Okon, B. Mfon, Tata Emmanuel
The Oil Mining License (OML) 26 Asset is in Isoko North Local Government Area, about 60km east of Warri in Delta State, an onshore asset in the northern Niger Delta. NPDC and FHN are partners for a joint operation of the mining lease and currently executes its function through an Asset Management Team (AMT), comprising employees of NPDC and FHN. The company (OML 26 JV) entered into a Global Memorandum of Understanding (GMOU) with OML 26 host communities to create an understanding and guide its relationship with the communities. The GMOU did not produced the desired result as OML 26 operations have often been interrupted by Community related issues. There is a lack of mutual trust on both sides and the Community and its agents tend to hold the company to ransom at the slightest opportunity. In a bid to reverse the trend, the AMT took the initiative to step back and assess the root cause of the acrimony, thoroughly engage the right elements within the Community to gauge their perspectives, and then developed a series of initiatives aimed at regaining the trust of the host communities. A framework is being developed that has engendered collaboration with the host communities (within its operating area) to build a mutually beneficial and symbiotic relationship that enables each party to achieve their goals and aspirations albeit in a peaceful, hitch free atmosphere. The AMT in line with the vision of the JV Partners is committed to sustainable community development, human capital development and capacity building, economic empowerment, and infrastructural growth. This paper highlights the key elements of the framework and the engagement strategies that has enabled the AMT to enjoy relative peace and operational stability while ramping up production and executing developmental projects in the communities.
石油开采许可证(OML) 26资产位于Isoko North Local Government Area，位于三角洲州Warri以东约60公里处，是尼日尔三角洲北部的陆上资产。NPDC和FHN是采矿租赁联合运营的合作伙伴，目前通过由NPDC和FHN员工组成的资产管理团队(AMT)执行其职能。该公司(OML 26合资公司)与OML 26主办社区签署了一份全球谅解备忘录(GMOU)，以建立谅解并指导其与社区的关系。GMOU没有产生预期的结果，因为OML 26的操作经常被与社区有关的问题中断。双方缺乏相互信任，社区及其代理人往往一有机会就会向公司勒索赎金。为了扭转这一趋势，AMT主动退后一步，评估恶语相向的根本原因，彻底让社区内的合适人士参与进来，评估他们的观点，然后制定了一系列旨在重新获得东道社区信任的举措。目前正在拟订一个框架，促成与东道社区(在其业务范围内)的合作，以建立一种互利和共生的关系，使每一方能够在和平、无阻碍的气氛中实现其目标和愿望。根据合资伙伴的愿景，AMT致力于可持续社区发展、人力资本开发和能力建设、经济赋权和基础设施增长。本文强调了框架和参与战略的关键要素，这些要素使AMT能够在提高生产和执行社区发展项目的同时享有相对的和平和运营稳定。
{"title":"Gains of an Effective Community Management Framework: The OML26 Experience","authors":"Blessyn Okpowo, Ebenezer Ageh, Peter Agodo, A. Okon, B. Mfon, Tata Emmanuel","doi":"10.2118/198802-MS","DOIUrl":"https://doi.org/10.2118/198802-MS","url":null,"abstract":"\u0000 The Oil Mining License (OML) 26 Asset is in Isoko North Local Government Area, about 60km east of Warri in Delta State, an onshore asset in the northern Niger Delta. NPDC and FHN are partners for a joint operation of the mining lease and currently executes its function through an Asset Management Team (AMT), comprising employees of NPDC and FHN.\u0000 The company (OML 26 JV) entered into a Global Memorandum of Understanding (GMOU) with OML 26 host communities to create an understanding and guide its relationship with the communities. The GMOU did not produced the desired result as OML 26 operations have often been interrupted by Community related issues. There is a lack of mutual trust on both sides and the Community and its agents tend to hold the company to ransom at the slightest opportunity. In a bid to reverse the trend, the AMT took the initiative to step back and assess the root cause of the acrimony, thoroughly engage the right elements within the Community to gauge their perspectives, and then developed a series of initiatives aimed at regaining the trust of the host communities. A framework is being developed that has engendered collaboration with the host communities (within its operating area) to build a mutually beneficial and symbiotic relationship that enables each party to achieve their goals and aspirations albeit in a peaceful, hitch free atmosphere. The AMT in line with the vision of the JV Partners is committed to sustainable community development, human capital development and capacity building, economic empowerment, and infrastructural growth. This paper highlights the key elements of the framework and the engagement strategies that has enabled the AMT to enjoy relative peace and operational stability while ramping up production and executing developmental projects in the communities.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83099697","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}
The use of Artificial Intelligence continues to grow in popularity within the geosciences in view of ever-growing complexity and magnitude of available subsurface data. This is equally evident by the need for faster and accurate interpretations required to find hydrocarbons in ever more challenging and increasingly complex basins. This drive is made necessary in a continuously evolving and cost conscious petroleum industry business environment. Advances in computing architecture now easily allows for more common application of machine learning techniques in day to day geoscience workflows. The use of machine learning in permeability prediction is becoming ever more common place as more specialists adopt this technique for modelling and prediction purposes. Typical machine learning techniques include Fuzzy Logic, Artificial Neural Networks (ANN) and Self Organizing Maps (SOM) amongst others which are run both in supervised and unsupervised modes. The described workflow in this paper was carried out using an available commercial standard petrophysical package with ANN built in modules. This paper describes a typical workflow for predicting reservoir permeability based on an integrated workflow utilizing core measurements integrated with available log data. Permeability is a key rock parameter for understanding fluid flow dynamics and flow rates and its modelling usually poses some unique challenges. Traditionally and statistically, this can be done at a fairly coarse level in cored wells by utilizing Poro-Perm correlations that usually do not capture fine scale variability observed at core scale measurement. These Poro-Perm transforms are subsequently applied on uncored wells to predict permeability. This paper analyses a workflow that aims to utilize a depth-normalized log and core data set trained using an Artificial Neural Network (ANN) module, blind tested on few key cored wells and subsequently used to predict permeability in uncored wells. In conclusion, the recommended workflow will ensure much more realistic and better matching permeability predictions.
{"title":"Machine Learning Application to Permeability Prediction Using Log & Core Measurements: A Realistic Workflow Application for Reservoir Characterization","authors":"Francis Eriavbe, Uzoamaka Okene","doi":"10.2118/198874-MS","DOIUrl":"https://doi.org/10.2118/198874-MS","url":null,"abstract":"\u0000 The use of Artificial Intelligence continues to grow in popularity within the geosciences in view of ever-growing complexity and magnitude of available subsurface data. This is equally evident by the need for faster and accurate interpretations required to find hydrocarbons in ever more challenging and increasingly complex basins. This drive is made necessary in a continuously evolving and cost conscious petroleum industry business environment.\u0000 Advances in computing architecture now easily allows for more common application of machine learning techniques in day to day geoscience workflows. The use of machine learning in permeability prediction is becoming ever more common place as more specialists adopt this technique for modelling and prediction purposes. Typical machine learning techniques include Fuzzy Logic, Artificial Neural Networks (ANN) and Self Organizing Maps (SOM) amongst others which are run both in supervised and unsupervised modes. The described workflow in this paper was carried out using an available commercial standard petrophysical package with ANN built in modules. This paper describes a typical workflow for predicting reservoir permeability based on an integrated workflow utilizing core measurements integrated with available log data.\u0000 Permeability is a key rock parameter for understanding fluid flow dynamics and flow rates and its modelling usually poses some unique challenges. Traditionally and statistically, this can be done at a fairly coarse level in cored wells by utilizing Poro-Perm correlations that usually do not capture fine scale variability observed at core scale measurement. These Poro-Perm transforms are subsequently applied on uncored wells to predict permeability. This paper analyses a workflow that aims to utilize a depth-normalized log and core data set trained using an Artificial Neural Network (ANN) module, blind tested on few key cored wells and subsequently used to predict permeability in uncored wells. In conclusion, the recommended workflow will ensure much more realistic and better matching permeability predictions.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87950090","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}
Edet Ita Okon, Joseph Adeoluwa Adetuberu, D. Appah
One of the most significant challenges for extending production life in mature waterflood fields is high water production. Couple with high reservoir heterogeneity, extensive layering and faulting, these fields often developed irregular flood patterns after decades of production which compounded the challenge to optimizing recovery from these fields. The severity of this problem can be seen in the Niger Delta oil fields where there are several matured fields that are producing at high water cut after many years of water flooding. The main objective of this study is to maximize oil recovery from a matured waterflood oil field while reducing the water cut. To achieve this objective, simulation studies were conducted on two cases scenarios. The first case was modelling and running waterflood simulation studied without applying pattern flood management (No PFM) while the second case scenario was done by exploring an automated pattern flood management (PFM). This was done with the aid of Petrel E&P software platform and ECLIPSE FrontSim to efficiently optimize the rate of water allocated to individual injectors. Using data from one of the oil fields operating in the Niger Delta, their performances were compared. The PFM gave the best result with a cumulative oil production of 30,727,470 STB when compared with the case of No PFM which gave a cumulative oil production of 26,968,224 STB (about 12% increase in oil recovery). The PFM water cut was 16% when compared with the case of No PFM which gave a water cut of 47% (about 63% reduction in water production). Hence, The PFM approach has made it possible to reduce water injection in more than 30% of the injectors while more than 62% of the producers experienced increase production and reduced water cut. The productivity increased upon automation of the workflow will enable engineers to identify the optimal injection allocation factors. It will also help engineers to understand and produce from the reservoir at an optimized decline rate and ensure the increase in ultimate recovery.
{"title":"Maximising Oil Recovery in Mature Water Floods Using Automated Pattern Flood Management","authors":"Edet Ita Okon, Joseph Adeoluwa Adetuberu, D. Appah","doi":"10.2118/198797-MS","DOIUrl":"https://doi.org/10.2118/198797-MS","url":null,"abstract":"\u0000 One of the most significant challenges for extending production life in mature waterflood fields is high water production. Couple with high reservoir heterogeneity, extensive layering and faulting, these fields often developed irregular flood patterns after decades of production which compounded the challenge to optimizing recovery from these fields. The severity of this problem can be seen in the Niger Delta oil fields where there are several matured fields that are producing at high water cut after many years of water flooding. The main objective of this study is to maximize oil recovery from a matured waterflood oil field while reducing the water cut. To achieve this objective, simulation studies were conducted on two cases scenarios. The first case was modelling and running waterflood simulation studied without applying pattern flood management (No PFM) while the second case scenario was done by exploring an automated pattern flood management (PFM). This was done with the aid of Petrel E&P software platform and ECLIPSE FrontSim to efficiently optimize the rate of water allocated to individual injectors. Using data from one of the oil fields operating in the Niger Delta, their performances were compared. The PFM gave the best result with a cumulative oil production of 30,727,470 STB when compared with the case of No PFM which gave a cumulative oil production of 26,968,224 STB (about 12% increase in oil recovery). The PFM water cut was 16% when compared with the case of No PFM which gave a water cut of 47% (about 63% reduction in water production). Hence, The PFM approach has made it possible to reduce water injection in more than 30% of the injectors while more than 62% of the producers experienced increase production and reduced water cut. The productivity increased upon automation of the workflow will enable engineers to identify the optimal injection allocation factors. It will also help engineers to understand and produce from the reservoir at an optimized decline rate and ensure the increase in ultimate recovery.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88921504","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}
Ejimofor Agbo, Chinedu Anyanwu, Oluwasola Olowoyeye, Titus Ini, Victor Emah
This paper demonstrates how 280ft of oil column spread unevenly across multiple and differentially depleted reservoir units separated by shale layers of varying thicknesses in a highly deviated (62 deg.) well was perforated in a one trip system and how the project cost was minimized by achieving multiple perforations in a single trip whilst retaining capacity to effectively cure losses and mitigating post-perforation well control risks. Against the conventional perforation methodology where reservoir units are perforated individually, isolated before carrying out the next perforation in the subsequent reservoir. The one trip system was designed and deployed in one run targeting all the 6 separate carefully selected sand lobes in one run ensuring good standoff from the contact and zonal isolation behind casing. Successful execution was confirmed with all the expected physical outcomes which includes pipe vibration, brine loss as well inspection of the spent guns. A post perforation noise and production logging also confirmed flow across all planned perforation intervals. Perforation of a highly deviated well in differentially depleted multi-lobed reservoirs present significant operational risks. This paper illustrates how one can safely collapse multiple conventional perforation runs into a single trip with its attendant benefits on cost efficiency, crossflow and well control. This is the first of its kind in a swampy terrain, shallow offshore Niger Delta.
{"title":"Single Trip Tubing Conveyed Perforations Across Multi-Lobed Differentially Depleted Reservoir Complexes In A Highly Deviated Well – Challenges, Lessons Learned & Best Practices","authors":"Ejimofor Agbo, Chinedu Anyanwu, Oluwasola Olowoyeye, Titus Ini, Victor Emah","doi":"10.2118/198757-MS","DOIUrl":"https://doi.org/10.2118/198757-MS","url":null,"abstract":"\u0000 This paper demonstrates how 280ft of oil column spread unevenly across multiple and differentially depleted reservoir units separated by shale layers of varying thicknesses in a highly deviated (62 deg.) well was perforated in a one trip system and how the project cost was minimized by achieving multiple perforations in a single trip whilst retaining capacity to effectively cure losses and mitigating post-perforation well control risks. Against the conventional perforation methodology where reservoir units are perforated individually, isolated before carrying out the next perforation in the subsequent reservoir. The one trip system was designed and deployed in one run targeting all the 6 separate carefully selected sand lobes in one run ensuring good standoff from the contact and zonal isolation behind casing. Successful execution was confirmed with all the expected physical outcomes which includes pipe vibration, brine loss as well inspection of the spent guns. A post perforation noise and production logging also confirmed flow across all planned perforation intervals. Perforation of a highly deviated well in differentially depleted multi-lobed reservoirs present significant operational risks. This paper illustrates how one can safely collapse multiple conventional perforation runs into a single trip with its attendant benefits on cost efficiency, crossflow and well control. This is the first of its kind in a swampy terrain, shallow offshore Niger Delta.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88579467","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}
Loretta Umeonaku, Philip Adegboye, Emmanuel Ubadigha, Hamza Ibrahim, Francis Anwana, Gabriel Omale
Formation Pressure data is a key parameter for in-depth characterization of a reservoir's potential and capacity to produce hydrocarbon. Pressure data are analyzed to confirm fluid interface, fluid type as well as to understand reservoir connectivity/isolation and compartmentalization if any, needed to finalise on the completion strategy to be utilized for optimal production. Acquisition of this data while drilling provides early and reliable information for decision making in optimising the drilling process. This paper demonstrates the use of Formation Pressure While Drilling (FPWD) tool to acquire formation pressure data. It examines the successful wellsite execution of FPWD service deployed in 3 deepwater wells in the Gulf of Guinea. It discusses operational sequence, quality of the results and how the operator utilized acquired data. In Well A, the test objective was to establish reservoir connectivity between a producer and an injector. For Well B, acquired pressure data was crucial in finalizing completion strategy. Well C shows how the direct pressure measurements were utilized to update the mud program in real time while drilling. Finally, this paper reemphasizes the value of FPWD by outlining how acquired pressure data met clients objectives by providing valuable quality data which provided great insight in reservoir characterization and safely drilling the wells to Total Depth.
{"title":"Realtime Aaquisition of Formation Pressure Data For Reservoir Characterization and Safe Drilling","authors":"Loretta Umeonaku, Philip Adegboye, Emmanuel Ubadigha, Hamza Ibrahim, Francis Anwana, Gabriel Omale","doi":"10.2118/198771-MS","DOIUrl":"https://doi.org/10.2118/198771-MS","url":null,"abstract":"\u0000 Formation Pressure data is a key parameter for in-depth characterization of a reservoir's potential and capacity to produce hydrocarbon. Pressure data are analyzed to confirm fluid interface, fluid type as well as to understand reservoir connectivity/isolation and compartmentalization if any, needed to finalise on the completion strategy to be utilized for optimal production. Acquisition of this data while drilling provides early and reliable information for decision making in optimising the drilling process.\u0000 This paper demonstrates the use of Formation Pressure While Drilling (FPWD) tool to acquire formation pressure data. It examines the successful wellsite execution of FPWD service deployed in 3 deepwater wells in the Gulf of Guinea. It discusses operational sequence, quality of the results and how the operator utilized acquired data. In Well A, the test objective was to establish reservoir connectivity between a producer and an injector. For Well B, acquired pressure data was crucial in finalizing completion strategy. Well C shows how the direct pressure measurements were utilized to update the mud program in real time while drilling.\u0000 Finally, this paper reemphasizes the value of FPWD by outlining how acquired pressure data met clients objectives by providing valuable quality data which provided great insight in reservoir characterization and safely drilling the wells to Total Depth.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77028315","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}
The ‘JEB’ oilfield has been in operation since 1992 with 24 oil producing Wells, 8 water injection Wells and no gas injection. From inception, the field was producing at the rate of 27 MSTB/D. The gas produced was 34,333.7 SCF/D which was being flared but later supplied to the Nigeria Liquefied Natural Gas (NLNG) for export. The field had very weak aquifer support and therefore had been water-flooded from early days of its production. With high water cut, it was necessary to find ways of reducing water production and increasing oil production. The study involved field data gathering, history matching of the field data and prediction of future production. Production rates from the different production schemes were simulated for fourteen years. The cumulative oil production of gas injection, water alternating gas (WAG) injection and gas alternating water (GAW) injection schemes were 4.28 MMMSTB, 3.29 MMMSTB and 3.15 MMMSTB respectively representing an incremental recovery of 38%, 6%, and 1%. The cumulative water production of gas injection, WAG injection and GAW injection were 2.65 MMMSTB, 6.52 MMMSTB and 6.90 MMMSTB respectively, which represent 64%, 10% and 5% reduction in produced water. The economic analysis showed gas injection as the best alternative injection scheme for the field with internal rate of return (IRR) of 19.26 %, while the IRR of WAG and GAW injection schemes were 12.09 % and 11.22 % respectively. Also, at 15% discount rate, the gas injection scheme had the best result with a Profitability Index (PI) greater than 1, a positive Net Present Value (NPV) while all other injection schemes had negative NPV and PI was less than one. The possibility of changing a field from water injection to gas injection has been explored, hence, before embarking on any enhanced oil recovery scheme, other alternatives should be evaluated.
{"title":"Switching from Water Injection Scheme to Gas Injection Scheme for Improved Oil Recovery in a Niger Delta Oilfield","authors":"J. Akpabio, B. E. Jackson, Celestine A. Udie","doi":"10.2118/198835-MS","DOIUrl":"https://doi.org/10.2118/198835-MS","url":null,"abstract":"\u0000 The ‘JEB’ oilfield has been in operation since 1992 with 24 oil producing Wells, 8 water injection Wells and no gas injection. From inception, the field was producing at the rate of 27 MSTB/D. The gas produced was 34,333.7 SCF/D which was being flared but later supplied to the Nigeria Liquefied Natural Gas (NLNG) for export. The field had very weak aquifer support and therefore had been water-flooded from early days of its production. With high water cut, it was necessary to find ways of reducing water production and increasing oil production. The study involved field data gathering, history matching of the field data and prediction of future production. Production rates from the different production schemes were simulated for fourteen years. The cumulative oil production of gas injection, water alternating gas (WAG) injection and gas alternating water (GAW) injection schemes were 4.28 MMMSTB, 3.29 MMMSTB and 3.15 MMMSTB respectively representing an incremental recovery of 38%, 6%, and 1%. The cumulative water production of gas injection, WAG injection and GAW injection were 2.65 MMMSTB, 6.52 MMMSTB and 6.90 MMMSTB respectively, which represent 64%, 10% and 5% reduction in produced water. The economic analysis showed gas injection as the best alternative injection scheme for the field with internal rate of return (IRR) of 19.26 %, while the IRR of WAG and GAW injection schemes were 12.09 % and 11.22 % respectively. Also, at 15% discount rate, the gas injection scheme had the best result with a Profitability Index (PI) greater than 1, a positive Net Present Value (NPV) while all other injection schemes had negative NPV and PI was less than one. The possibility of changing a field from water injection to gas injection has been explored, hence, before embarking on any enhanced oil recovery scheme, other alternatives should be evaluated.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76921524","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}
C. Ndokwu, K. Amadi, Oluwaseun Toyobo, Victor Okowi, I. Ajisafe, A. Inenemo
Due to the low oil price, Exploration and Production (E&P) companies are driven to reduce the cost per barrel of oil equivalent (BOE). The application of reservoir navigation services, in the placement of high angle and horizontal (HAHZ) wells in the sweet spot of reservoirs, has aided in meeting this economic need of the E&P, while also improving hydrocarbon recovery. Reservoir navigation services (RNS) can be regarded as another tool for improving the odds of success while drilling of HAHZ wells. This service involves the integration of real-time data (deep-reading azimuthal resistivity, gamma-ray, density image, resistivity image logs, near bit inclination and a fit for purpose rotary steerable system) to accurately position the well-bore relative to specific subsurface targets, while remaining within the constraints of the drilling and completion program. RNS also require a software package capable of pre-well modeling, displaying the acquired real-time data and interactively adapting the model to the real-time data. Geosteering in Njaba field involved a comprehensive pre-well planning, discussions, documentation and management approved decision-tree. Using three wells for this study, this paper describes the challenges, procedures and results of geosteering in Njaba Field located on-shore Niger-Delta. From different entry points, wells NJX1, NJX2, and NJX3 were planned to drain the same reservoir and optimize hydrocarbon recovery within the reservoir. Some of the challenges encountered includes geosteering the wellbore above a pre-determined production TVD hardline while simultaneously avoiding drilling into an overlying undulating shale cap rock, vertical seismic uncertainty and undulating formation boundaries.
{"title":"Reservoir Navigation in Njaba Field – Challenges, Procedure and Results","authors":"C. Ndokwu, K. Amadi, Oluwaseun Toyobo, Victor Okowi, I. Ajisafe, A. Inenemo","doi":"10.2118/198786-MS","DOIUrl":"https://doi.org/10.2118/198786-MS","url":null,"abstract":"\u0000 Due to the low oil price, Exploration and Production (E&P) companies are driven to reduce the cost per barrel of oil equivalent (BOE). The application of reservoir navigation services, in the placement of high angle and horizontal (HAHZ) wells in the sweet spot of reservoirs, has aided in meeting this economic need of the E&P, while also improving hydrocarbon recovery.\u0000 Reservoir navigation services (RNS) can be regarded as another tool for improving the odds of success while drilling of HAHZ wells. This service involves the integration of real-time data (deep-reading azimuthal resistivity, gamma-ray, density image, resistivity image logs, near bit inclination and a fit for purpose rotary steerable system) to accurately position the well-bore relative to specific subsurface targets, while remaining within the constraints of the drilling and completion program. RNS also require a software package capable of pre-well modeling, displaying the acquired real-time data and interactively adapting the model to the real-time data.\u0000 Geosteering in Njaba field involved a comprehensive pre-well planning, discussions, documentation and management approved decision-tree. Using three wells for this study, this paper describes the challenges, procedures and results of geosteering in Njaba Field located on-shore Niger-Delta. From different entry points, wells NJX1, NJX2, and NJX3 were planned to drain the same reservoir and optimize hydrocarbon recovery within the reservoir. Some of the challenges encountered includes geosteering the wellbore above a pre-determined production TVD hardline while simultaneously avoiding drilling into an overlying undulating shale cap rock, vertical seismic uncertainty and undulating formation boundaries.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"130 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79239227","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 Well with plug set in both tubing was sabotaged and even after initially capping the well, it was observed that attempting to kill the Target Well via surface pumping was abortive. Therefore, in order to achieve well control, drilling a relief well became imperative and required some critical decision to be taken. This include location selection, type fluid to be used in drilling, the casing setting depth, downhole measuring tools for use, as well as contractors needed in achieving success in a suitation of incomplete well survey data. This paper presents how this keys needs were met in drilling the Relief Well planned for 97days trouble free and performed in 107days from spud to hitting Target Well. The success was on single attempt in spite of it having an incomplete survey record acquired 49 years earlier.
{"title":"Efficient Placement of Relief Well Using Combination of Tools","authors":"A. Pedro, D. Feltracco, A. Pasquale, E. Gravante","doi":"10.2118/198760-MS","DOIUrl":"https://doi.org/10.2118/198760-MS","url":null,"abstract":"\u0000 A Well with plug set in both tubing was sabotaged and even after initially capping the well, it was observed that attempting to kill the Target Well via surface pumping was abortive.\u0000 Therefore, in order to achieve well control, drilling a relief well became imperative and required some critical decision to be taken. This include location selection, type fluid to be used in drilling, the casing setting depth, downhole measuring tools for use, as well as contractors needed in achieving success in a suitation of incomplete well survey data.\u0000 This paper presents how this keys needs were met in drilling the Relief Well planned for 97days trouble free and performed in 107days from spud to hitting Target Well. The success was on single attempt in spite of it having an incomplete survey record acquired 49 years earlier.","PeriodicalId":11250,"journal":{"name":"Day 3 Wed, August 07, 2019","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83759393","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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