One of the challenges of the petroleum industry is achieving maximum recovery from oil reservoirs. The natural energy of the reservoir, primary recoveries in most cases do not exceed 20%. To improve recovery, secondary recovery techniques are employed. With secondary recovery techniques such as waterflooding, an incremental recovery ranging from 15 to 25% can be achieved. Several theories and methods have been developed for predicting waterflood performance. The Dykstra-Parson technique stands as the most widely used of these methods. The authors developed a discrete, analytical solution from which the vertical coverage, water-oil ratio, cumulative oil produced, cumulative water produced and injected, and the time required for injection was determined. Reznik et al extended the work of Dykstra and Parson to include exact, analytical, continuous solutions, with explicit solutions for time, constant injection pressure, and constant overall injection rate conditions, property time, real or process time, with the assumption of piston-like displacement. This work presents a computer implementation to compare the results of the Dykstra and Parson method, and the Reznik et al extension. A user-friendly graphical user interface executable application has been developed for both methods using Python 3. The application provides an interactive GUI output for graphs and tables with the python matplotlib module, and Pandastable. The GUI was built with Tkinter and converted to an executable desktop application using Pyinstaller and the Nullsoft Scriptable Install System, to serve as a hands-on tool for petroleum engineers and the industry. The results of the program for both methods gave a close match with that obtained from the simulation performed with Flow (Open Porous Media). The results provided more insight into the underlying principles and applications of the methods.
{"title":"Computer Implementation of the Dykstra-Parsons Method of Waterflood Calculation","authors":"P. Lekia","doi":"10.2118/207151-ms","DOIUrl":"https://doi.org/10.2118/207151-ms","url":null,"abstract":"\u0000 One of the challenges of the petroleum industry is achieving maximum recovery from oil reservoirs. The natural energy of the reservoir, primary recoveries in most cases do not exceed 20%. To improve recovery, secondary recovery techniques are employed. With secondary recovery techniques such as waterflooding, an incremental recovery ranging from 15 to 25% can be achieved. Several theories and methods have been developed for predicting waterflood performance.\u0000 The Dykstra-Parson technique stands as the most widely used of these methods. The authors developed a discrete, analytical solution from which the vertical coverage, water-oil ratio, cumulative oil produced, cumulative water produced and injected, and the time required for injection was determined. Reznik et al extended the work of Dykstra and Parson to include exact, analytical, continuous solutions, with explicit solutions for time, constant injection pressure, and constant overall injection rate conditions, property time, real or process time, with the assumption of piston-like displacement.\u0000 This work presents a computer implementation to compare the results of the Dykstra and Parson method, and the Reznik et al extension. A user-friendly graphical user interface executable application has been developed for both methods using Python 3. The application provides an interactive GUI output for graphs and tables with the python matplotlib module, and Pandastable. The GUI was built with Tkinter and converted to an executable desktop application using Pyinstaller and the Nullsoft Scriptable Install System, to serve as a hands-on tool for petroleum engineers and the industry.\u0000 The results of the program for both methods gave a close match with that obtained from the simulation performed with Flow (Open Porous Media). The results provided more insight into the underlying principles and applications of the methods.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84891212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a model for assessing Subsea Control Module (SCM) integrity for re-use after decommissioning. The SCM is one of the most failure-prone components in subsea oil and gas developments, and although a relatively inexpensive component in a Subsea Production System (SPS), the failure of an SCM can require production to be ceased, significantly impacting project economics. The re-use of decommissioned SCMs could improve the economics of subsea oil and gas projects by reducing design and manufacturing lead times, improving production availability, and enabling the economic exploitation of both marginal and mature fields. Insights gained through relevant literature, industry standards, and subsea industry experts led to the development of the Integrity Assessment Model for Decommissioned Subsea Control Modules proposed in this paper. The model is based on an Integrity Assessment process as well as a Risk-Based Compatibility Assessment. Discussions include a background of the SCM and common failures, the economics of SCM re-use, and Applications for the re-use of SCMs. The Integrity Assessment Model is described in detail, as well as the benefits and limitations. Areas of future research in support of subsea equipment re-use are identified, including improvements to reliability databases for subsea equipment, and the creation of a quantitative metric describing subsea equipment integrity.
{"title":"A Suitable Model for Assessing the Integrity of Subsea Control Modules SCMs for Re-Use after Decommissioning","authors":"Erica Root, J. Andrawus, I. Iyalla","doi":"10.2118/207205-ms","DOIUrl":"https://doi.org/10.2118/207205-ms","url":null,"abstract":"\u0000 This paper proposes a model for assessing Subsea Control Module (SCM) integrity for re-use after decommissioning. The SCM is one of the most failure-prone components in subsea oil and gas developments, and although a relatively inexpensive component in a Subsea Production System (SPS), the failure of an SCM can require production to be ceased, significantly impacting project economics. The re-use of decommissioned SCMs could improve the economics of subsea oil and gas projects by reducing design and manufacturing lead times, improving production availability, and enabling the economic exploitation of both marginal and mature fields. Insights gained through relevant literature, industry standards, and subsea industry experts led to the development of the Integrity Assessment Model for Decommissioned Subsea Control Modules proposed in this paper. The model is based on an Integrity Assessment process as well as a Risk-Based Compatibility Assessment. Discussions include a background of the SCM and common failures, the economics of SCM re-use, and Applications for the re-use of SCMs. The Integrity Assessment Model is described in detail, as well as the benefits and limitations. Areas of future research in support of subsea equipment re-use are identified, including improvements to reliability databases for subsea equipment, and the creation of a quantitative metric describing subsea equipment integrity.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"329 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79722492","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}
Pressure transient analysis has been used to evaluate performance of a vertical well located within two intersecting sealing faults. The nature and types of boundary affect productivity in bounded reservoirs. Well performance is strongly affected by well location with respect to the boundary, be it single, paired and parallel or paired and inclined. The goal of this research was to study pressure behavior as well as performance of a vertical well located within two intersecting sealing faults inclined at various angles θ and at unequal distances to faults. Unlike similar works previously carried out, this work can be used to study or predict pressure distribution of a well in a wedge system located at unequal distances to faults. Using the concept of images, the study proposed new models for estimating distances between image well(s) and active well. These models were applied in the solution to the dimensionless diffusivity equation to characterize pressure transient behavior of a well located at unequal distances to the inclined faults. These pressures and pressure derivatives were computed from the total pressure drop expression summing all the image wells by the principle of superposition. The MATLAB, Python and Excel software were deployed to compute all the dimensionless pressures for the different well designs. The results obtained show that 1) the proposed models give accurate estimation of active well distances to image wells; 2) the models show that the distance between the active and image wells d0,i increases for the range of values of angles 0°< θ0,i ≤ 180° and decreases for the range 180° < θ0,i < 360°; 3) the relationship between unequal well distances and productivity has a maximum point; 4) beyond this point, the well ceases to be productive and; 5) this maximum point is at equal distances of the well from both faults, in this case, 15 ft. Larger magnitudes of dimensionless pressure derivatives would indicate higher oil production for any well design and inclination of the boundaries. Worthy of future works are similar studies on 1) horizontal wells and 2) mixed boundaries, that is, one sealing fault and one constant pressure boundary.
{"title":"Pressures and Pressure Derivatives of a Vertical Well Located Within Two Inclined Faults: Case Study of Basic Angles and Unequal Well Distances from Faults","authors":"M. Ojah, S. Adewole","doi":"10.2118/207138-ms","DOIUrl":"https://doi.org/10.2118/207138-ms","url":null,"abstract":"\u0000 Pressure transient analysis has been used to evaluate performance of a vertical well located within two intersecting sealing faults. The nature and types of boundary affect productivity in bounded reservoirs. Well performance is strongly affected by well location with respect to the boundary, be it single, paired and parallel or paired and inclined. The goal of this research was to study pressure behavior as well as performance of a vertical well located within two intersecting sealing faults inclined at various angles θ and at unequal distances to faults. Unlike similar works previously carried out, this work can be used to study or predict pressure distribution of a well in a wedge system located at unequal distances to faults. Using the concept of images, the study proposed new models for estimating distances between image well(s) and active well. These models were applied in the solution to the dimensionless diffusivity equation to characterize pressure transient behavior of a well located at unequal distances to the inclined faults. These pressures and pressure derivatives were computed from the total pressure drop expression summing all the image wells by the principle of superposition. The MATLAB, Python and Excel software were deployed to compute all the dimensionless pressures for the different well designs. The results obtained show that 1) the proposed models give accurate estimation of active well distances to image wells; 2) the models show that the distance between the active and image wells d0,i increases for the range of values of angles 0°< θ0,i ≤ 180° and decreases for the range 180° < θ0,i < 360°; 3) the relationship between unequal well distances and productivity has a maximum point; 4) beyond this point, the well ceases to be productive and; 5) this maximum point is at equal distances of the well from both faults, in this case, 15 ft. Larger magnitudes of dimensionless pressure derivatives would indicate higher oil production for any well design and inclination of the boundaries. Worthy of future works are similar studies on 1) horizontal wells and 2) mixed boundaries, that is, one sealing fault and one constant pressure boundary.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77806696","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}
Production ramp-up can be a tricky exercise, with a repertoire of challenges and surprises, which can threaten the proposed percentage of success. These challenges largely stem from paucity of data, change in reservoir dynamics, impact of unauthorized third-party activities and the compliment of skill sets/experience in the team. In addition, reservoir models are in some cases, ineffective tools for reservoir management and prediction. This is especially true in assets that are heavily bunkered by crude oil thieves and in geologically complex reservoirs with very few wells. Therefore, models must be updated with recent data and new understanding, to remain useful and accurate. Of great importance to a successful production ramp-up effort is assembling an integrated team of experienced sub-surface professionals and field executors. Unfortunately, in some teams and companies, the position and opinions of Geologists are often overlooked, resulting in mixed outcomes. Geologists do not only think in "millions of years" but can add value and contribute significantly to the overall project objective. This paper explores and explains the role of a geologist, as part of an integrated asset management team, in the successful ramp-up of production from 45KOPD to about 80KOPD, without drilling a single well or executing any rig activity. It also showcases some work methodologies adopted in the evaluation of candidate wells and the power inherent in adopting an integrated subsurface approach.
{"title":"Project 80KOPD: A Geologist's Perspective to a Successful Production Ramp-Up Effort.","authors":"Valentine Ihebuzor","doi":"10.2118/207123-ms","DOIUrl":"https://doi.org/10.2118/207123-ms","url":null,"abstract":"\u0000 Production ramp-up can be a tricky exercise, with a repertoire of challenges and surprises, which can threaten the proposed percentage of success. These challenges largely stem from paucity of data, change in reservoir dynamics, impact of unauthorized third-party activities and the compliment of skill sets/experience in the team. In addition, reservoir models are in some cases, ineffective tools for reservoir management and prediction. This is especially true in assets that are heavily bunkered by crude oil thieves and in geologically complex reservoirs with very few wells. Therefore, models must be updated with recent data and new understanding, to remain useful and accurate. Of great importance to a successful production ramp-up effort is assembling an integrated team of experienced sub-surface professionals and field executors. Unfortunately, in some teams and companies, the position and opinions of Geologists are often overlooked, resulting in mixed outcomes. Geologists do not only think in \"millions of years\" but can add value and contribute significantly to the overall project objective. This paper explores and explains the role of a geologist, as part of an integrated asset management team, in the successful ramp-up of production from 45KOPD to about 80KOPD, without drilling a single well or executing any rig activity. It also showcases some work methodologies adopted in the evaluation of candidate wells and the power inherent in adopting an integrated subsurface approach.","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":"81519465","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}
During multiphase flow, there is a variation of the physical distribution of the phases within the conduit leading to different flow regimes and consequently variation in the pressure gradient along with the flow regime, hence flow parameter is of vital importance in the prediction of flow regime and pressure gradient in multiphase flow. Analytical solutions and empirical correlations have been developed to predict the flow regime and the pressure gradient respectively. However, in this study, we seek to use supervised machine learning to make predictions taking parameters such as relative phase volume, bulk fluid flow rates, individual phase flow rates, conduit diameters, inclination, phase densities and temperature as input to the model. The data representing these parameters can be regularly updated to reflect the flow conditions in the well. The flow is composed of water, oil and air at different temperatures. The machine learning models used are Logistic Regression, Decision Trees and Principal Component Analysis. The first two is supervised and are tuned for accuracy dependent on pressure gauge readings while the third seeks to determine the parameters of greatest influence on the predicted output, the flow regime and pressure gradient. The model is constrained to learning and making predictions for fluid production through the tubing only. The trained model shows promise for application in the industry as it allows for automation of systems used to control flow and affords a more comprehensive approach to mitigating flow problems in pipeline systems and flow systems in oilfields.
{"title":"Investigating the Use of Machine Learning Models for the Prediction of Pressure Gradient and Flow Regimes in Multiphase Flow in Horizontal Pipes","authors":"Isemin. A. Isemin, King-Akanimo B. Nkundu","doi":"10.2118/208410-ms","DOIUrl":"https://doi.org/10.2118/208410-ms","url":null,"abstract":"\u0000 During multiphase flow, there is a variation of the physical distribution of the phases within the conduit leading to different flow regimes and consequently variation in the pressure gradient along with the flow regime, hence flow parameter is of vital importance in the prediction of flow regime and pressure gradient in multiphase flow. Analytical solutions and empirical correlations have been developed to predict the flow regime and the pressure gradient respectively. However, in this study, we seek to use supervised machine learning to make predictions taking parameters such as relative phase volume, bulk fluid flow rates, individual phase flow rates, conduit diameters, inclination, phase densities and temperature as input to the model. The data representing these parameters can be regularly updated to reflect the flow conditions in the well. The flow is composed of water, oil and air at different temperatures. The machine learning models used are Logistic Regression, Decision Trees and Principal Component Analysis. The first two is supervised and are tuned for accuracy dependent on pressure gauge readings while the third seeks to determine the parameters of greatest influence on the predicted output, the flow regime and pressure gradient.\u0000 The model is constrained to learning and making predictions for fluid production through the tubing only. The trained model shows promise for application in the industry as it allows for automation of systems used to control flow and affords a more comprehensive approach to mitigating flow problems in pipeline systems and flow systems in oilfields.","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":"78827924","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}
There are numerous problems encountered during drilling such as wellbore instability, drilling mud weight estimation, as well as selecting good casing and bit for the drilling operations. It is therefore important to understand and accurately determine the strength of the rock in order to avoid these common drilling problems which are mostly encountered during well operations. It is of paramount importance to determine uniaxial compressive strength (UCS) from core and sonic log data so as to accurately predict rock strength for better well planning. In this work, we were able to obtain a correlation to determine UCS from data obtained from ten (10) wells in different locations in onshore Niger Delta using the regression analysis method. The correlation of UCS versus Poisson's ratio gave R2 value of 90.0%. The R2- value tending towards one (1) indicates that this model can be reliably used to predict ND-UCS and the p<0.05 shows that there is significant relationship between ND-UCS and Poisson's ratio. The model was validated with an entirely different well data and it predicted over 89% rock UCS data when compared to the actual rock UCS data. This study also provides an understanding of the variation in UCS and Poisson's ratio with depth for effective rock property analysis and evaluation. These correlations will help well engineers to make informed decisions on rock strength predictions during well planning and operations as well as manage wellbore stability optimally.
{"title":"Efficient Wellbore Optimization Through Rock Property Analysis and Evaluation","authors":"Joshua Oluwayomi Ogunrinde","doi":"10.2118/207111-ms","DOIUrl":"https://doi.org/10.2118/207111-ms","url":null,"abstract":"\u0000 There are numerous problems encountered during drilling such as wellbore instability, drilling mud weight estimation, as well as selecting good casing and bit for the drilling operations. It is therefore important to understand and accurately determine the strength of the rock in order to avoid these common drilling problems which are mostly encountered during well operations. It is of paramount importance to determine uniaxial compressive strength (UCS) from core and sonic log data so as to accurately predict rock strength for better well planning. In this work, we were able to obtain a correlation to determine UCS from data obtained from ten (10) wells in different locations in onshore Niger Delta using the regression analysis method. The correlation of UCS versus Poisson's ratio gave R2 value of 90.0%. The R2- value tending towards one (1) indicates that this model can be reliably used to predict ND-UCS and the p<0.05 shows that there is significant relationship between ND-UCS and Poisson's ratio. The model was validated with an entirely different well data and it predicted over 89% rock UCS data when compared to the actual rock UCS data. This study also provides an understanding of the variation in UCS and Poisson's ratio with depth for effective rock property analysis and evaluation. These correlations will help well engineers to make informed decisions on rock strength predictions during well planning and operations as well as manage wellbore stability optimally.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"101 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77270841","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}
Celestine A. Udie, F. Faithpraise, Agnes Anuka, E. Ana
Crude oil pollution is a serious threat to both humans and agricultural trends in all ramifications. The effects include suffocation of humans, plants and other useful organisms in the polluted area. The resultant effect is that it is cost effective and provides an aerated soil environment for enough nutrient distribution. This research designed an effective reagent that has ability to destroy the crude oil molecules in the soil and reviewed highlights for crude oil molecule conversion into soil nutrient. The formulation is based on the principle of complete destruction or combustion of hydrocarbons (crude oil) molecules. The Reagent is called hydrocarbons polluted area sludge solution. The advantage is that the polluted soil is remediated and it is restored after the application of the reagent, with increase in its original fertility. The reagent was applied on a soil polluted by crude oil around Warri Refinery and the result showed a complete destruction of the sludge molecules. It converted the sludge molecules into organic salt, hydride and water molecules. It was equally used on samples sludge from Ogoni polluted area and the result was successful. The sludge was completely destroyed and converted into organic salts and acids. Soil and water samples around the polluted area analysis result revealed that contaminated soil and water were restored. It has been confirmed that the reagent has the ability to destroy sludge molecules in soil, effectively clean and restore the soil with added fertility.
{"title":"Oil Polluted Soil Remediation Techniques Using a Complete Molecules Destruction Formulated Reagent","authors":"Celestine A. Udie, F. Faithpraise, Agnes Anuka, E. Ana","doi":"10.2118/207107-ms","DOIUrl":"https://doi.org/10.2118/207107-ms","url":null,"abstract":"\u0000 Crude oil pollution is a serious threat to both humans and agricultural trends in all ramifications. The effects include suffocation of humans, plants and other useful organisms in the polluted area. The resultant effect is that it is cost effective and provides an aerated soil environment for enough nutrient distribution. This research designed an effective reagent that has ability to destroy the crude oil molecules in the soil and reviewed highlights for crude oil molecule conversion into soil nutrient. The formulation is based on the principle of complete destruction or combustion of hydrocarbons (crude oil) molecules. The Reagent is called hydrocarbons polluted area sludge solution. The advantage is that the polluted soil is remediated and it is restored after the application of the reagent, with increase in its original fertility. The reagent was applied on a soil polluted by crude oil around Warri Refinery and the result showed a complete destruction of the sludge molecules. It converted the sludge molecules into organic salt, hydride and water molecules. It was equally used on samples sludge from Ogoni polluted area and the result was successful. The sludge was completely destroyed and converted into organic salts and acids. Soil and water samples around the polluted area analysis result revealed that contaminated soil and water were restored. It has been confirmed that the reagent has the ability to destroy sludge molecules in soil, effectively clean and restore the soil with added fertility.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75207637","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}
In order to properly meet up with the ever-increasing demand for petroleum products worldwide, it has become increasingly necessary to produce oil and gas fields more economically and efficiently. Waterflooding is currently the most widely used secondary recovery method to improve oil recovery after primary depletion. A crucial component required to conduct an efficient waterflooding operation is an optimal production setting, most especially with respect to the amount of water involved. This research work has been carried out to develop a model that can be used to maximize oil recovery and minimize water production with the least amount and number of waterflood variables in order to minimize the secondary recovery investment cost. The gradient-based approach to optimize the production and net present value (NPV) from a waterflood reservoir using the flow rates or bottom hole pressures of the production wells as the controlling factors with the use of smart well technology was applied. In this approach, a variant of the optimal switching time technique was used in the optimization process to equalize the arrival times of the waterfront at multiple producers, thereby increasing the cumulative oil production. The optimization procedure involved maximizing the objective function (NPV) by adjusting a set of manipulated variables (flow rates). The optimal pressure profile of the waterflood scenario that gave the maximum NPV was obtained as the solution to the waterflood problem. The proposed optimization methodology was applied to a waterflood process carried out on a reservoir field developed by a five-spot recovery design in the Niger Delta area of Nigeria, which was used as a case study. The forward run was carried out with a commercial reservoir oil simulator. The results of the waterflood optimization revealed that an increase in the net present value of up to 9.7% and an increase in cumulative production of up to 30% from the base case could be achieved.
{"title":"Assessment and Optimization of Waterflooding Performance in a Hydrocarbon Reservoir","authors":"Miracle Imwonsa Osatemple, A. Adeniyi, A. Giwa","doi":"10.2118/207114-ms","DOIUrl":"https://doi.org/10.2118/207114-ms","url":null,"abstract":"\u0000 In order to properly meet up with the ever-increasing demand for petroleum products worldwide, it has become increasingly necessary to produce oil and gas fields more economically and efficiently. Waterflooding is currently the most widely used secondary recovery method to improve oil recovery after primary depletion. A crucial component required to conduct an efficient waterflooding operation is an optimal production setting, most especially with respect to the amount of water involved. This research work has been carried out to develop a model that can be used to maximize oil recovery and minimize water production with the least amount and number of waterflood variables in order to minimize the secondary recovery investment cost. The gradient-based approach to optimize the production and net present value (NPV) from a waterflood reservoir using the flow rates or bottom hole pressures of the production wells as the controlling factors with the use of smart well technology was applied. In this approach, a variant of the optimal switching time technique was used in the optimization process to equalize the arrival times of the waterfront at multiple producers, thereby increasing the cumulative oil production. The optimization procedure involved maximizing the objective function (NPV) by adjusting a set of manipulated variables (flow rates). The optimal pressure profile of the waterflood scenario that gave the maximum NPV was obtained as the solution to the waterflood problem. The proposed optimization methodology was applied to a waterflood process carried out on a reservoir field developed by a five-spot recovery design in the Niger Delta area of Nigeria, which was used as a case study. The forward run was carried out with a commercial reservoir oil simulator. The results of the waterflood optimization revealed that an increase in the net present value of up to 9.7% and an increase in cumulative production of up to 30% from the base case could be achieved.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79077106","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}
Virtue Urunwo Elechi, S. S. Ikiensikimama, J. Ajienka, O. Akaranta, O. Okon, D. Chris
Gas hydrates are known impediments to flow. Mitigation of gas hydrates in deep offshore with accessibility issues is by chemical injection. This paper considers the effect of 2-Di(methylamino) ethylmethacrylate (2-DMAEM) a kinetic gas hydrate inhibitor and a Local Inhibitor (LI) on Clarias gariepinus, a marine organism. The assessment was done using Random Complete Block Design (RCBD), a standard method of toxicity testing. Its effect was compared to that of a local Inhibitor (LI). The test carried out showed that at the end of the exposure period, 2-DMAEM caused 100% mortality in concentrations of 10 and 100ml/L and had significant differences in water parameters across the row as concentration increased. The LI caused 0% mortality in same concentration ranges and had no significant differences as concentrations increased across the row. 2-DMAEM should be discarded as an inhibitor given its inherent danger while LI should be harnessed and developed as gas hydrate inhibitor.
{"title":"Eco-Toxicity of 2-Di Methylamino Ethylmethacrylate 2-DMAEM as a Commercial Kinetic Hydrate Inhibitor KHI","authors":"Virtue Urunwo Elechi, S. S. Ikiensikimama, J. Ajienka, O. Akaranta, O. Okon, D. Chris","doi":"10.2118/207156-ms","DOIUrl":"https://doi.org/10.2118/207156-ms","url":null,"abstract":"\u0000 Gas hydrates are known impediments to flow. Mitigation of gas hydrates in deep offshore with accessibility issues is by chemical injection. This paper considers the effect of 2-Di(methylamino) ethylmethacrylate (2-DMAEM) a kinetic gas hydrate inhibitor and a Local Inhibitor (LI) on Clarias gariepinus, a marine organism. The assessment was done using Random Complete Block Design (RCBD), a standard method of toxicity testing. Its effect was compared to that of a local Inhibitor (LI). The test carried out showed that at the end of the exposure period, 2-DMAEM caused 100% mortality in concentrations of 10 and 100ml/L and had significant differences in water parameters across the row as concentration increased. The LI caused 0% mortality in same concentration ranges and had no significant differences as concentrations increased across the row. 2-DMAEM should be discarded as an inhibitor given its inherent danger while LI should be harnessed and developed as gas hydrate inhibitor.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79643454","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}
Valentine Ihebuzor, O. Onyeneke, A. Adebari, Obasi Ogbonnaya
Reserves are typically estimated and re-validated throughout the life of a producing field. The accuracy of this estimation is based on the availability of relevant and current data from that reservoir or field and other factors. There are several methods for estimating reserves, but the choice of which method is to be applied is often based on the data available per time. However, these methods are known to be associated with varying degrees of uncertainties arising from quality of data, the assumptions adopted and the experience of the evaluator. The biggest uncertainty in reserve estimation lies in the inability of the commonly available methods to estimate and discount the huge volumes lost due to unauthorized production by third parties, through crude oil theft, illegal bunkering activities, and spills. This leads to the gross overestimation of reserves and the economic viability of an asset, especially in onshore and shallow offshore assets where such illegal activities are typical and rampant. This paper showcases an approach of estimating reserves, through the integration of multidisciplinary data, which enables the estimation and discounting of crude oil volumes lost due to illegal production from a reservoir.
{"title":"An Approach to Estimating Reserve Volumes by Discounting Unauthorized Production Via Crude Oil Theft","authors":"Valentine Ihebuzor, O. Onyeneke, A. Adebari, Obasi Ogbonnaya","doi":"10.2118/207110-ms","DOIUrl":"https://doi.org/10.2118/207110-ms","url":null,"abstract":"\u0000 Reserves are typically estimated and re-validated throughout the life of a producing field. The accuracy of this estimation is based on the availability of relevant and current data from that reservoir or field and other factors. There are several methods for estimating reserves, but the choice of which method is to be applied is often based on the data available per time. However, these methods are known to be associated with varying degrees of uncertainties arising from quality of data, the assumptions adopted and the experience of the evaluator. The biggest uncertainty in reserve estimation lies in the inability of the commonly available methods to estimate and discount the huge volumes lost due to unauthorized production by third parties, through crude oil theft, illegal bunkering activities, and spills. This leads to the gross overestimation of reserves and the economic viability of an asset, especially in onshore and shallow offshore assets where such illegal activities are typical and rampant. This paper showcases an approach of estimating reserves, through the integration of multidisciplinary data, which enables the estimation and discounting of crude oil volumes lost due to illegal production from a reservoir.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89414696","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：