David Rafael Contreras Perez, C. Sellar, A. Valente
The implementation of Artificial Intelligence and Machine Learning algorithms has introduced the opportunity for alternative techniques to estimate permeability within uncored intervals/wells. Different combinations of input data and different approaches for training values were evaluated to select a consistent predictive model able to produce permeability logs while honoring the geological concept and available core permeability measurements. The approach presented here is deployed in a low porosity, low permeability hydrocarbon bearing carbonate reservoir with a limited dataset, aiming to estimate a permeability log from available wireline log and core data. The geological description from core in Reservoir 3 indicates the presence of oil saturation in mud-dominated carbonate rocks with a moderate degree of calcite cementation. After a rigorous quality check of the available permeability measurements from conventional core analysis data, a high confidence database of porosity and permeability measurements were combined with existing wireline logs (e.g. GR, Resistivity, Neutron Porosity and Archie Water Saturation). The resulting structured dataset was used for permeability prediction using Random Forest regression (from scikit-learn in python). Three cases of permeability logs were generated from this methodology at well log resolution to be used in static reservoir modeling and saturation-height-modeling with J-functions. The permeability and saturation height models are key inputs for dynamic modelling to generate production forecasts in this undeveloped reservoir. Three different permeability models were trained using 144 high quality core plug measurements from six cored wells. Even though the number of available samples can be considered low for a machine learning workflow, an oversampling approach with point repetition was adopted to overcome data insufficiency for this dataset. From an E & P point of view, accurately predicting reservoir permeability in hydrocarbon reservoirs has been one of the major challenges facing the industry for decades. The approach outlined here reduces uncertainty in permeability prediction in the uncored interval. Furthermore, since permeability is part of the estimation of water saturation, this approach reduces uncertainty in water saturation interpretation, the potential deliverability of flow units and the volumetrics.
人工智能和机器学习算法的实施为估算未取心段/井的渗透率提供了替代技术的机会。对输入数据的不同组合和不同的训练方法进行了评估，以选择一个一致的预测模型，该模型能够在尊重地质概念和可用岩心渗透率测量的同时生成渗透率测井曲线。该方法应用于低孔隙度、低渗透含烃碳酸盐岩储层，数据有限，旨在通过现有的电缆测井和岩心数据估算渗透率。3号储层岩心地质描述表明，泥质碳酸盐岩中存在含油饱和度，方解石胶结程度中等。在对常规岩心分析数据中可用渗透率测量数据进行严格的质量检查后，将孔隙度和渗透率测量数据与现有的电缆测井数据(例如GR、电阻率、中子孔隙度和Archie含水饱和度)相结合，形成一个高可信度的数据库。所得到的结构化数据集使用随机森林回归(来自scikit-learn in python)进行渗透率预测。该方法在测井分辨率下生成了三例渗透率测井，用于静态储层建模和j函数的饱和度-高度建模。渗透率和饱和高度模型是该未开发油藏进行动态建模以进行产量预测的关键输入。利用来自6口取心井的144口高质量岩心塞测量数据，训练了3种不同的渗透率模型。尽管对于机器学习工作流来说，可用样本的数量可能被认为很低，但采用了点重复的过采样方法来克服该数据集的数据不足。从e&p的角度来看，几十年来，准确预测储层渗透率一直是油气行业面临的主要挑战之一。本文概述的方法减少了未取心层段渗透率预测的不确定性。此外，由于渗透率是含水饱和度估计的一部分，这种方法减少了含水饱和度解释、流动单元的潜在产能和体积的不确定性。
{"title":"Permeability Estimation Using Machine Learning Techniques for a Heterogeneous Mud Dominated Carbonate Reservoir, Offshore UAE","authors":"David Rafael Contreras Perez, C. Sellar, A. Valente","doi":"10.2118/214400-ms","DOIUrl":"https://doi.org/10.2118/214400-ms","url":null,"abstract":"The implementation of Artificial Intelligence and Machine Learning algorithms has introduced the opportunity for alternative techniques to estimate permeability within uncored intervals/wells. Different combinations of input data and different approaches for training values were evaluated to select a consistent predictive model able to produce permeability logs while honoring the geological concept and available core permeability measurements. The approach presented here is deployed in a low porosity, low permeability hydrocarbon bearing carbonate reservoir with a limited dataset, aiming to estimate a permeability log from available wireline log and core data. The geological description from core in Reservoir 3 indicates the presence of oil saturation in mud-dominated carbonate rocks with a moderate degree of calcite cementation. After a rigorous quality check of the available permeability measurements from conventional core analysis data, a high confidence database of porosity and permeability measurements were combined with existing wireline logs (e.g. GR, Resistivity, Neutron Porosity and Archie Water Saturation). The resulting structured dataset was used for permeability prediction using Random Forest regression (from scikit-learn in python). Three cases of permeability logs were generated from this methodology at well log resolution to be used in static reservoir modeling and saturation-height-modeling with J-functions. The permeability and saturation height models are key inputs for dynamic modelling to generate production forecasts in this undeveloped reservoir. Three different permeability models were trained using 144 high quality core plug measurements from six cored wells. Even though the number of available samples can be considered low for a machine learning workflow, an oversampling approach with point repetition was adopted to overcome data insufficiency for this dataset. From an E & P point of view, accurately predicting reservoir permeability in hydrocarbon reservoirs has been one of the major challenges facing the industry for decades. The approach outlined here reduces uncertainty in permeability prediction in the uncored interval. Furthermore, since permeability is part of the estimation of water saturation, this approach reduces uncertainty in water saturation interpretation, the potential deliverability of flow units and the volumetrics.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"399 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116226693","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}
Safa Al Ismaili, C. Gaol, Nils Langanke, L. Ganzer
This work introduces an efficient approach in addition to the traditional scheme of polymer screening for the application of enhanced oil recovery. Microfluidics technology which requires less sample volumes, and less time consumption, is applied to the polymer screening procedure. This approach delivers an efficient screening process and enables the upscaling of polymer flow behavior in porous media. This work investigates three commercial polymer products, A, B, and C, which vary in average molecular weight at shear rate (0.1 – 1000 s−1) and temperature (20°C– 60°C). Fifteen polymer solutions with different concentrations are made from the three products and screened through three evaluation stages. The first stage is measuring the bulk shear viscosity of the polymer solutions in the rheometer. The second stage is conducting single-phase polymer flooding through a novel micromodel. The stage of this approach applies the results from the earlier stages by running two-phase flooding experiments that implement polymer flooding for reservoir conditions of an oil field in Oman. The micromodel structure used in this work is generated based on X-ray micro-computed tomography (μCT) images of a Bentheimer core plug. Thus, the micromodel's porosity, permeability, pore, and grain size distribution are similar to the core plug. This characteristic gives an upscaling potential to a larger scale, such as core plug or even a field implementation. A database with bulk shear viscosity and model fits (Power law & Carreau) is generated from the rheometer measurements for polymers A, B, and C. A novel 3D surface model that relates the shear rate, temperature, bulk viscosity, and concentration is developed from the data in the first stage. The single-phase flooding experiments allow the investigation of the behavior of polymer in porous media under shear and extensional flow. Furthermore, the comparison of bulk shear viscosity and in-situ viscosity shows the potential to support the analysis of an empirical constant (C-factor). In addition, polymer injectivity and retention are investigated by analyzing the pressure drop and residual resistance factor after each single-phase polymer flooding experiment. The last stage of this work provides the improvement of displacement efficiency and the recovery factor, which measures the success of the approach. The novelty of this approach is the utilization of the linear Bentheimer micromodel for delivering an efficient polymer screening process. This micromodel reflects similar rock properties as Bentheimer rocks, which provide the potential to upscale the results from microfluidics to reservoir rocks. In addition, the novel 3D surface model developed in this work allows comprehensive screening, which is accomplished through combining the parameters required in polymer evaluation at one domain.
本文介绍了在传统聚合物筛分方案之外的一种提高采收率的有效方法。微流控技术应用于聚合物筛选过程中，需要较少的样品体积和较少的时间消耗。这种方法提供了一种高效的筛选过程，并使聚合物在多孔介质中的流动行为得以提升。本研究研究了三种商业聚合物产品，A, B和C，它们在剪切速率(0.1 - 1000 s−1)和温度(20°C - 60°C)下的平均分子量变化。将这三种产品制成15种不同浓度的聚合物溶液，并通过三个评价阶段进行筛选。第一阶段是在流变仪中测量聚合物溶液的整体剪切粘度。第二阶段是通过一种新的微模型进行单相聚合物驱。该方法的阶段应用了阿曼某油田油藏条件下进行的两阶段驱油实验的结果。本工作中使用的微模型结构是基于Bentheimer芯塞的x射线微计算机断层扫描(μCT)图像生成的。因此，微观模型的孔隙度、渗透率、孔隙度和粒度分布与岩心塞相似。这一特性使其具有扩大规模的潜力，例如岩心桥塞甚至现场实施。根据聚合物A、B和c的流变仪测量数据，生成了一个具有整体剪切粘度和模型拟合(Power law & Carreau)的数据库。根据第一阶段的数据，开发了一个新的3D表面模型，该模型将剪切速率、温度、整体粘度和浓度联系起来。单相驱实验可以研究聚合物在剪切和拉伸流动下在多孔介质中的行为。此外，体剪切粘度和原位粘度的比较显示了支持经验常数(c因子)分析的潜力。此外，通过分析每次单相聚合物驱实验后的压降和残余阻力系数，考察了聚合物的注入性和滞留性。最后一阶段的工作是提高驱替效率和采收率，以此来衡量该方法的成功与否。这种方法的新颖之处在于利用线性Bentheimer微模型来提供有效的聚合物筛选过程。该微观模型反映了与Bentheimer岩石相似的岩石性质，这提供了将微流体结果提升到储层岩石的潜力。此外，在这项工作中开发的新型3D表面模型允许全面筛选，这是通过在一个领域结合聚合物评估所需的参数来完成的。
{"title":"Utilization of Microfluidics Technology for an Efficient Polymer Screening Process in Enhanced Oil Recovery (EOR) Applications","authors":"Safa Al Ismaili, C. Gaol, Nils Langanke, L. Ganzer","doi":"10.2118/214444-ms","DOIUrl":"https://doi.org/10.2118/214444-ms","url":null,"abstract":"\u0000 This work introduces an efficient approach in addition to the traditional scheme of polymer screening for the application of enhanced oil recovery. Microfluidics technology which requires less sample volumes, and less time consumption, is applied to the polymer screening procedure. This approach delivers an efficient screening process and enables the upscaling of polymer flow behavior in porous media.\u0000 This work investigates three commercial polymer products, A, B, and C, which vary in average molecular weight at shear rate (0.1 – 1000 s−1) and temperature (20°C– 60°C). Fifteen polymer solutions with different concentrations are made from the three products and screened through three evaluation stages. The first stage is measuring the bulk shear viscosity of the polymer solutions in the rheometer. The second stage is conducting single-phase polymer flooding through a novel micromodel. The stage of this approach applies the results from the earlier stages by running two-phase flooding experiments that implement polymer flooding for reservoir conditions of an oil field in Oman. The micromodel structure used in this work is generated based on X-ray micro-computed tomography (μCT) images of a Bentheimer core plug. Thus, the micromodel's porosity, permeability, pore, and grain size distribution are similar to the core plug. This characteristic gives an upscaling potential to a larger scale, such as core plug or even a field implementation.\u0000 A database with bulk shear viscosity and model fits (Power law & Carreau) is generated from the rheometer measurements for polymers A, B, and C. A novel 3D surface model that relates the shear rate, temperature, bulk viscosity, and concentration is developed from the data in the first stage. The single-phase flooding experiments allow the investigation of the behavior of polymer in porous media under shear and extensional flow. Furthermore, the comparison of bulk shear viscosity and in-situ viscosity shows the potential to support the analysis of an empirical constant (C-factor). In addition, polymer injectivity and retention are investigated by analyzing the pressure drop and residual resistance factor after each single-phase polymer flooding experiment. The last stage of this work provides the improvement of displacement efficiency and the recovery factor, which measures the success of the approach.\u0000 The novelty of this approach is the utilization of the linear Bentheimer micromodel for delivering an efficient polymer screening process. This micromodel reflects similar rock properties as Bentheimer rocks, which provide the potential to upscale the results from microfluidics to reservoir rocks. In addition, the novel 3D surface model developed in this work allows comprehensive screening, which is accomplished through combining the parameters required in polymer evaluation at one domain.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114219060","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 present work introduces an efficient workflow for AI-enhanced decision-making in Field Development Planning Optimization. Despite the clear importance of uncertainty quantification in decision-making, we find that constraints in time, hardware, and costs are often limiting factors during field evaluation, with the drawback of having a biased uncertainty description or a wrong risk perception. The proposed work encompasses history matching, solution analysis, and production optimization with special emphasis on reducing both simulation and processing time, maximizing what we can call the result per core hour. At the center of our work is an AI-guided optimizer suited to avoid excessive convergence bias and maintain an optimal exploration vs. exploitation performance. The optimizer allows the integration of a multi-objective (MO) formulation in standard history matching and optimization workflows. Despite the flexibility of MO optimization and the vast literature in the energy industry, its usage in real-field cases has always been quite limited due to its formulation availability in commercial software and the increased computation time. This work will show improvement in solution accuracy and formulation flexibility compared to Single Objective (SO) formulations at no increase in runtime. MO is based on the iterative convergence of an efficient frontier from the results generated by the simulation. This same concept has been brought to a user analysis step to allow the identification of best solutions across multiple evaluation workflows, lowering the expertise level for a solution.
{"title":"Efficient FDP Optimization for AI Enhanced Decision Making","authors":"G. de Paola, Richar Villarroel Danger","doi":"10.2118/214345-ms","DOIUrl":"https://doi.org/10.2118/214345-ms","url":null,"abstract":"\u0000 The present work introduces an efficient workflow for AI-enhanced decision-making in Field Development Planning Optimization. Despite the clear importance of uncertainty quantification in decision-making, we find that constraints in time, hardware, and costs are often limiting factors during field evaluation, with the drawback of having a biased uncertainty description or a wrong risk perception. The proposed work encompasses history matching, solution analysis, and production optimization with special emphasis on reducing both simulation and processing time, maximizing what we can call the result per core hour.\u0000 At the center of our work is an AI-guided optimizer suited to avoid excessive convergence bias and maintain an optimal exploration vs. exploitation performance. The optimizer allows the integration of a multi-objective (MO) formulation in standard history matching and optimization workflows. Despite the flexibility of MO optimization and the vast literature in the energy industry, its usage in real-field cases has always been quite limited due to its formulation availability in commercial software and the increased computation time. This work will show improvement in solution accuracy and formulation flexibility compared to Single Objective (SO) formulations at no increase in runtime.\u0000 MO is based on the iterative convergence of an efficient frontier from the results generated by the simulation. This same concept has been brought to a user analysis step to allow the identification of best solutions across multiple evaluation workflows, lowering the expertise level for a solution.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125416409","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}
Josias Pereira de Oliveira, S. Santos, Antônio Alberto Souza dos Santos, D. Schiozer
Many projects in the Brazilian pre-salt assume the use of water alternating gas (WAG-CO2) injection as an ecologically safe carbon storage strategy, with improved hydrocarbon recovery. However, studies that compare these advantages with a simpler management plan are not common. The objective of this work is to compare WAG-CO2 injection with continuous injection of water and gas (CIWG) rich in CO2 in separate wells for the development and management of a light-oil fractured carbonate reservoir subject to full gas recycling. We employed the UNISIM-II benchmark model, a naturally fractured carbonate reservoir with Brazilian pre-salt characteristics, which enables an application in controlled environment where the reference response is known (UNISIM-II-R). We used a model-based decision analysis for production strategy selection, hierarchical optimization of the decision variables and algorithms to maximize the objective function. Representative models (RM) are selected from the ensemble of models and used to incorporate the effects of geological, reservoir, and operational uncertainties into the optimization process. The net present value is the objective function during the nominal optimization of candidate strategies of each RM and the expected monetary value and risk analysis are considered to select the final production strategy considering uncertainties. The risk analysis was quantified based on downside risk and upside potential relation to a benchmark return. We optimized two alternative development plans (one considering WAG-CO2 injection and the other continuous injection of water and gas in separate wells) and compared their performance indicators and decision variables, including design variables (number, type and placement of well, and size of production facilities) and life-cycle control rules (management of equipment over time). We then applied a cross-simulation, where the best strategy optimized for one recovery method was applied to the other and the injection strategy was optimized again. We were therefore able to assess the need to pre-define the recovery method before defining design variables to validate the flexibility of each strategy for possible future changes in the recovery mechanism. Finally, we repeated the study for different reservoir scenarios to compare the alternatives considering typical uncertainties of the Brazilian pre-salt and validated the final strategies in the reference model to quantify the real value in decision making. The strategies reached a full gas recycling in both recovery methods and allowed a comparison of their advantages and disadvantages. The operations of WAG-CO2 injection can be more complex and the equipment more expensive. The novelty of this work is the consideration of continuous injection of water and gas in separate wells as a simpler alternative to the development and management of pre-salt oil fields, since this method may also meet operators’ and environmental demands, bearing sim
{"title":"Comparing WAG-CO2 Injection with Continuous Water and Gas Injection in Separate Wells for the Development and Management of a CO2-Rich Light Oil Fractured Carbonate Reservoir Subject to Full Gas Recycling","authors":"Josias Pereira de Oliveira, S. Santos, Antônio Alberto Souza dos Santos, D. Schiozer","doi":"10.2118/214421-ms","DOIUrl":"https://doi.org/10.2118/214421-ms","url":null,"abstract":"\u0000 Many projects in the Brazilian pre-salt assume the use of water alternating gas (WAG-CO2) injection as an ecologically safe carbon storage strategy, with improved hydrocarbon recovery. However, studies that compare these advantages with a simpler management plan are not common. The objective of this work is to compare WAG-CO2 injection with continuous injection of water and gas (CIWG) rich in CO2 in separate wells for the development and management of a light-oil fractured carbonate reservoir subject to full gas recycling. We employed the UNISIM-II benchmark model, a naturally fractured carbonate reservoir with Brazilian pre-salt characteristics, which enables an application in controlled environment where the reference response is known (UNISIM-II-R). We used a model-based decision analysis for production strategy selection, hierarchical optimization of the decision variables and algorithms to maximize the objective function. Representative models (RM) are selected from the ensemble of models and used to incorporate the effects of geological, reservoir, and operational uncertainties into the optimization process. The net present value is the objective function during the nominal optimization of candidate strategies of each RM and the expected monetary value and risk analysis are considered to select the final production strategy considering uncertainties. The risk analysis was quantified based on downside risk and upside potential relation to a benchmark return. We optimized two alternative development plans (one considering WAG-CO2 injection and the other continuous injection of water and gas in separate wells) and compared their performance indicators and decision variables, including design variables (number, type and placement of well, and size of production facilities) and life-cycle control rules (management of equipment over time). We then applied a cross-simulation, where the best strategy optimized for one recovery method was applied to the other and the injection strategy was optimized again. We were therefore able to assess the need to pre-define the recovery method before defining design variables to validate the flexibility of each strategy for possible future changes in the recovery mechanism. Finally, we repeated the study for different reservoir scenarios to compare the alternatives considering typical uncertainties of the Brazilian pre-salt and validated the final strategies in the reference model to quantify the real value in decision making. The strategies reached a full gas recycling in both recovery methods and allowed a comparison of their advantages and disadvantages. The operations of WAG-CO2 injection can be more complex and the equipment more expensive. The novelty of this work is the consideration of continuous injection of water and gas in separate wells as a simpler alternative to the development and management of pre-salt oil fields, since this method may also meet operators’ and environmental demands, bearing sim","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114508111","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. Perez-Perez, C. Romero, E. Santanach-Carreras, A. Skauge
The injection of alkali in acidic viscous oils is known to promote the in-situ formation of emulsions during chemical oil recovery. Naphthenic acid components react with the alkali to form in-situ surfactants, which support oil emulsification at the water-oil interface. It is believed that emulsification and transport of the dispersed oil in the presence of polymer can significantly improve oil recovery. In earlier work, we proposed a new mechanistic non-equilibrium model to simulate alkali-polymer processes for different oil viscosities (2000 – 3500 cP at 50°C) with an acid number of around 4 mg KOH/g. The model considers emulsion generation kinetics, polymer, and emulsion non-Newtonian viscosity through a straightforward modelling strategy. The emulsified oil was treated as a dispersed component in water phase (O/W emulsion), while the water phase mobility considered the apparent aqueous phase viscosity containing dispersed oil and polymer. In the above referenced work, seven alkali-polymer corefloods performed with different alkali types and slug sizes were history matched. We showed that the model is capable of appropriately matching the experiments. Kinetics obtained by history match show that emulsion formation under the conditions here studied is alkali type dependent. In the current work, we applied our alkali-polymer model in two displacement tests (Hele Shaw cell) with two different oil viscosities (2000 – 200 cP at 50°C). These new experiments included secondary water flood, tertiary polymer flood and quaternary alkali-polymer flood. The initial conditions of alkali-polymer (AP) flood were obtained after properly modelling the unstable immiscible floods and polymer floods. For modelling the polymer floods (2D slabs), three models were evaluated: 1) extension of relative permeability curves applied to water flood, 2) Killough method (hysteresis for the water phase) and relative permeability power-law extensions and 3) two relative permeability curves with polymer concentration dependency. Our alkali-polymer model was employed for simultaneously history matching 1D and 2D experiments performed with 5 g/L of Na2CO3 and polymer. When comparing alkali-polymer results, a good agreement was found for the complete set of experiments. In addition, fitting parameters (kinetics and emulsion viscosity) were close to the parameters reported in the earlier study. Finally, fitted alkali-polymer parameters were employed for predicting alkali-polymer outputs in the second slab (with similar alkali-polymer concentration but lower oil viscosity). Even if experimental observations are relatively well represented, a lower value of incremental oil recovery (<3 % OOIP) was obtained. We believe that the use of a less viscous oil (diluted oil) in the experiments may influence the generation and transport of formed emulsions.
{"title":"Simulations of Alkali-Polymer Experiments: Modeling of In-Situ Emulsion Generation and Transport of Oil-In-Water Emulsion in Porous Media","authors":"A. Perez-Perez, C. Romero, E. Santanach-Carreras, A. Skauge","doi":"10.2118/214429-ms","DOIUrl":"https://doi.org/10.2118/214429-ms","url":null,"abstract":"\u0000 The injection of alkali in acidic viscous oils is known to promote the in-situ formation of emulsions during chemical oil recovery. Naphthenic acid components react with the alkali to form in-situ surfactants, which support oil emulsification at the water-oil interface. It is believed that emulsification and transport of the dispersed oil in the presence of polymer can significantly improve oil recovery.\u0000 In earlier work, we proposed a new mechanistic non-equilibrium model to simulate alkali-polymer processes for different oil viscosities (2000 – 3500 cP at 50°C) with an acid number of around 4 mg KOH/g. The model considers emulsion generation kinetics, polymer, and emulsion non-Newtonian viscosity through a straightforward modelling strategy. The emulsified oil was treated as a dispersed component in water phase (O/W emulsion), while the water phase mobility considered the apparent aqueous phase viscosity containing dispersed oil and polymer.\u0000 In the above referenced work, seven alkali-polymer corefloods performed with different alkali types and slug sizes were history matched. We showed that the model is capable of appropriately matching the experiments. Kinetics obtained by history match show that emulsion formation under the conditions here studied is alkali type dependent.\u0000 In the current work, we applied our alkali-polymer model in two displacement tests (Hele Shaw cell) with two different oil viscosities (2000 – 200 cP at 50°C). These new experiments included secondary water flood, tertiary polymer flood and quaternary alkali-polymer flood. The initial conditions of alkali-polymer (AP) flood were obtained after properly modelling the unstable immiscible floods and polymer floods. For modelling the polymer floods (2D slabs), three models were evaluated: 1) extension of relative permeability curves applied to water flood, 2) Killough method (hysteresis for the water phase) and relative permeability power-law extensions and 3) two relative permeability curves with polymer concentration dependency.\u0000 Our alkali-polymer model was employed for simultaneously history matching 1D and 2D experiments performed with 5 g/L of Na2CO3 and polymer. When comparing alkali-polymer results, a good agreement was found for the complete set of experiments. In addition, fitting parameters (kinetics and emulsion viscosity) were close to the parameters reported in the earlier study.\u0000 Finally, fitted alkali-polymer parameters were employed for predicting alkali-polymer outputs in the second slab (with similar alkali-polymer concentration but lower oil viscosity). Even if experimental observations are relatively well represented, a lower value of incremental oil recovery (<3 % OOIP) was obtained. We believe that the use of a less viscous oil (diluted oil) in the experiments may influence the generation and transport of formed emulsions.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"124 2-3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133107003","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}
M. Moradi, W. Garcia, Percy Martin Amado, M. Konopczynski
Growing energy demand heightened by climate change challenges has seen the oil and gas industry tightly embrace smarter and more sustainable technologies. The motivation is to quickly grasp net-zero targets, while safely optimising oil-gas production. By its nature, the industry has the ingenuity to eliminate unnecessary carbon emissions. However, traditional development plans relied on the use of wells with minimal or no emphasis on the well completion in terms of optimum deliverability. This would produce a mixture of oil and excessive unwanted fluids such as water and/or gas which requires costly energy-intensive processes. Although the process has been optimized to some extent and often re-injects these unwanted fluids back to the reservoir, there has been not enough attention to the environmental impacts as these repetitive treatment processes of the fluids results in discharging excessive and unnecessary Greenhouse Gas (GHG) into the atmosphere. The issue is now widely recognized to be one of the industry challenges in its drive toward net-zero energy delivery. A case study of a heavy crude oil field with a strong water drive, located in a natural reserve in the Marañon basin of the Peruvian Amazon is presented. Here, the implementation of autonomous inflow control devices (AICDs) technology, through a knowledge management process, has made it possible to significantly reduce the volumes of water produced, which are reinjected again, thus generating significant savings in fluid lifting, treatment and energy consumption associated with the operations in this field. The study introduces a workflow that uses a publicly available GHG footprint estimator to evaluate the carbon intensity of different oil and gas field development plans. The estimator predicts the amount of GHG emitted from any individual operation, process and treatment involved in a field development from exploration to delivery at the gate of a refinery. Having this calculation enables the operators to recognize the major GHG emitter operations and optimise the process toward net zero using new technologies, methods and/or workflows. The workflow has then been applied to the field located in the Peruvian Amazon to illustrate the significant impact of flow control technologies on the reduction of GHG emissions and achieving net-zero targets. For example, the amounts of carbon intensity, GHG emission and energy consumption from the field have been estimated to been reduced by up to 56%, 64% and 78% respectively with AICD completions compared to a case of non-AICD completion such as stand-alone screen (SAS) was installed in the wells instead. This study provides the engineers with a workflow to quantify the impacts of the use of new technologies especially flow control devices. It also illustrates the significant role of flow control technologies in achieving net-zero production.
{"title":"Delivering NET ZERO– A Case Study of Minimized Carbon Intensity Production Using Autonomous Inflow Control Technologies from a Remote Location in the Peruvian Amazon","authors":"M. Moradi, W. Garcia, Percy Martin Amado, M. Konopczynski","doi":"10.2118/214343-ms","DOIUrl":"https://doi.org/10.2118/214343-ms","url":null,"abstract":"\u0000 Growing energy demand heightened by climate change challenges has seen the oil and gas industry tightly embrace smarter and more sustainable technologies. The motivation is to quickly grasp net-zero targets, while safely optimising oil-gas production.\u0000 By its nature, the industry has the ingenuity to eliminate unnecessary carbon emissions. However, traditional development plans relied on the use of wells with minimal or no emphasis on the well completion in terms of optimum deliverability. This would produce a mixture of oil and excessive unwanted fluids such as water and/or gas which requires costly energy-intensive processes. Although the process has been optimized to some extent and often re-injects these unwanted fluids back to the reservoir, there has been not enough attention to the environmental impacts as these repetitive treatment processes of the fluids results in discharging excessive and unnecessary Greenhouse Gas (GHG) into the atmosphere. The issue is now widely recognized to be one of the industry challenges in its drive toward net-zero energy delivery.\u0000 A case study of a heavy crude oil field with a strong water drive, located in a natural reserve in the Marañon basin of the Peruvian Amazon is presented. Here, the implementation of autonomous inflow control devices (AICDs) technology, through a knowledge management process, has made it possible to significantly reduce the volumes of water produced, which are reinjected again, thus generating significant savings in fluid lifting, treatment and energy consumption associated with the operations in this field.\u0000 The study introduces a workflow that uses a publicly available GHG footprint estimator to evaluate the carbon intensity of different oil and gas field development plans. The estimator predicts the amount of GHG emitted from any individual operation, process and treatment involved in a field development from exploration to delivery at the gate of a refinery. Having this calculation enables the operators to recognize the major GHG emitter operations and optimise the process toward net zero using new technologies, methods and/or workflows. The workflow has then been applied to the field located in the Peruvian Amazon to illustrate the significant impact of flow control technologies on the reduction of GHG emissions and achieving net-zero targets. For example, the amounts of carbon intensity, GHG emission and energy consumption from the field have been estimated to been reduced by up to 56%, 64% and 78% respectively with AICD completions compared to a case of non-AICD completion such as stand-alone screen (SAS) was installed in the wells instead.\u0000 This study provides the engineers with a workflow to quantify the impacts of the use of new technologies especially flow control devices. It also illustrates the significant role of flow control technologies in achieving net-zero production.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130559354","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 obtain the actual gas-water relative permeability of the coalbed methane (CBM) reservoir and further deepen the cognition of the gas-water production law of multiple coal seams, a relative permeability calculation method based on production data inversion is constructed. Based on production data, historical fitting is carried out through the multiple coal seams whole process coupling flow model, and the basic physical parameters of each layer are inversed. Based on the obtained physical parameters, the productivity prediction of the whole production cycle is carried out. By calculating the average water saturation and gas-water relative permeability in each iteration time step, the average gas-water relative permeability curve of the reservoir in the target period is finally obtained. The results show that the calculation method proposed in this paper can realize the acquisition of the relative permeability curve in the given period. Compared with the input relative permeability curve, there is a reverse point on the output relative permeability curve that can represent the continuous production of desorption gas. Gas production is affected significantly by different types of initial input relative permeability curves, and is mainly influenced by the input relative permeability curve at the initial production stage. Under ±30% deviation, the average difference in cumulative gas production is 16.92% (3 years). During the production of CBM wells, the average water saturation was maintained at a high level. At the end of the production of multiple coal seams commingled production well, the average water saturation change is less than 15%. Restricted by high water saturation, the average relative permeability of the gas is always maintained at a low level, less than 0.1 at the end of production of actual production wells. The fundamental technical difficulty in realizing the initial high production and subsequent sustained and stable production of CBM wells lies in how to reduce the reservoir water saturation effectively and improve the relative permeability of the gas, so as to promote the desorption of adsorbed gas and the sustained CBM production.
{"title":"Research on Multiple Coal Seams Relative Permeability Calculation Method Based on Production Data Inversion","authors":"Tianhao Huang, Zhiming Wang, Quanshu Zeng","doi":"10.2118/214422-ms","DOIUrl":"https://doi.org/10.2118/214422-ms","url":null,"abstract":"\u0000 To obtain the actual gas-water relative permeability of the coalbed methane (CBM) reservoir and further deepen the cognition of the gas-water production law of multiple coal seams, a relative permeability calculation method based on production data inversion is constructed. Based on production data, historical fitting is carried out through the multiple coal seams whole process coupling flow model, and the basic physical parameters of each layer are inversed. Based on the obtained physical parameters, the productivity prediction of the whole production cycle is carried out. By calculating the average water saturation and gas-water relative permeability in each iteration time step, the average gas-water relative permeability curve of the reservoir in the target period is finally obtained. The results show that the calculation method proposed in this paper can realize the acquisition of the relative permeability curve in the given period. Compared with the input relative permeability curve, there is a reverse point on the output relative permeability curve that can represent the continuous production of desorption gas. Gas production is affected significantly by different types of initial input relative permeability curves, and is mainly influenced by the input relative permeability curve at the initial production stage. Under ±30% deviation, the average difference in cumulative gas production is 16.92% (3 years). During the production of CBM wells, the average water saturation was maintained at a high level. At the end of the production of multiple coal seams commingled production well, the average water saturation change is less than 15%. Restricted by high water saturation, the average relative permeability of the gas is always maintained at a low level, less than 0.1 at the end of production of actual production wells. The fundamental technical difficulty in realizing the initial high production and subsequent sustained and stable production of CBM wells lies in how to reduce the reservoir water saturation effectively and improve the relative permeability of the gas, so as to promote the desorption of adsorbed gas and the sustained CBM production.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125926679","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. Scerbacova, Dmitrii Pereponov, Michael A. Tarkhov, V. Kazaku, A. Rykov, Ivan Filippov, E. Zenova, V. Krutko, A. Cheremisin, E. Shilov
Surfactant flooding is among the most studied and widespread EOR technologies that is being introduced into tight and low-permeable reservoirs to mobilize trapped oil. Typically, the selection of formulations for chemical flooding is associated with numerous challenges and constraints such as time-consuming core flooding tests, the high cost of the tests with modern saturation control methods, and a limited amount of core samples. To overcome these issues, microfluidic technology was applied to optimize the screening of surfactant compositions for flooding. The workflow of this project consisted of five main steps: (1) fabrication of microfluidic chips, (2) surfactant screening in bulk, (3) surfactant flooding in microfluidic chips, (4) image analysis and data interpretation. Silicon-glass microfluidic chips, which are 2D representatives of the reservoir porous media, were used in the experiments. The porous structure geometry was developed based on CT images of core samples from a particular field with low permeability. For the selected surfactants, interfacial behavior on the boundary with n-decane was studied and correlated with hydrocarbon recovery ability. The results obtained revealed that the IFT patterns have a significant influence on displacement efficiency. Thus, the surfactant compositions with a lower initial IFT than the equilibrium value achieved higher recovery factors.
{"title":"Visualization of Surfactant Flooding in Tight Reservoir Using Microfluidics","authors":"A. Scerbacova, Dmitrii Pereponov, Michael A. Tarkhov, V. Kazaku, A. Rykov, Ivan Filippov, E. Zenova, V. Krutko, A. Cheremisin, E. Shilov","doi":"10.2118/214419-ms","DOIUrl":"https://doi.org/10.2118/214419-ms","url":null,"abstract":"Surfactant flooding is among the most studied and widespread EOR technologies that is being introduced into tight and low-permeable reservoirs to mobilize trapped oil. Typically, the selection of formulations for chemical flooding is associated with numerous challenges and constraints such as time-consuming core flooding tests, the high cost of the tests with modern saturation control methods, and a limited amount of core samples. To overcome these issues, microfluidic technology was applied to optimize the screening of surfactant compositions for flooding. The workflow of this project consisted of five main steps: (1) fabrication of microfluidic chips, (2) surfactant screening in bulk, (3) surfactant flooding in microfluidic chips, (4) image analysis and data interpretation.\u0000 Silicon-glass microfluidic chips, which are 2D representatives of the reservoir porous media, were used in the experiments. The porous structure geometry was developed based on CT images of core samples from a particular field with low permeability. For the selected surfactants, interfacial behavior on the boundary with n-decane was studied and correlated with hydrocarbon recovery ability. The results obtained revealed that the IFT patterns have a significant influence on displacement efficiency. Thus, the surfactant compositions with a lower initial IFT than the equilibrium value achieved higher recovery factors.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129899419","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}
Maria Isabel Trujillo, P. Veen, Waldemar Szemat-Vielma, Esther Escobar-Burnham
Australia has embarked on a fast race to become the leading hydrogen provider in the Asia Pacific, supported by countries such as Japan and South Korea as firm customers. The seven territories of Australia are developing their business strategies to achieve competitiveness and a place in the race. A strategy based on a strengths, weakness, opportunities, and threats (SWOT) analysis has been derived from each territory, considering the current state-of-the-art hydrogen technologies and their main drivers. These strategies have been benchmarked against the Australia Council National Hydrogen Strategy and the Australia Electricity Market Operator Strategy regarding the scenario of a hydrogen superpower for Australia to become an essential player in the hydrogen market using the IBA (Interactive Bundle Analysis) framework. The seven territories’ strategies were analyzed, and a set of recommendations are derived from this analysis with the aim to reinforce each territory strategy, providing the Australian Federal Government a framework to assess which project to finance projects first and assist in de-risking them to attract private capital, which is essential for the country to become a large-scale hydrogen producer and exporter. This analysis recommends that should Australia focus on the development of blue hydrogen first and secures market share via Western Australia using steam methane reformer (SMR) and Victoria with the brown coal gasification, both fitted with the corresponding carbon capture and storage (CCS). In parallel, the Australian Federal government should incentivize Tasmania to produce green hydrogen followed by Queensland and Western Australia while other territories need to develop as per their individual strengths.
{"title":"The Race to Conquer the Hydrogen Business: The Seven Territories of Australia's Strategy","authors":"Maria Isabel Trujillo, P. Veen, Waldemar Szemat-Vielma, Esther Escobar-Burnham","doi":"10.2118/214426-ms","DOIUrl":"https://doi.org/10.2118/214426-ms","url":null,"abstract":"\u0000 Australia has embarked on a fast race to become the leading hydrogen provider in the Asia Pacific, supported by countries such as Japan and South Korea as firm customers. The seven territories of Australia are developing their business strategies to achieve competitiveness and a place in the race.\u0000 A strategy based on a strengths, weakness, opportunities, and threats (SWOT) analysis has been derived from each territory, considering the current state-of-the-art hydrogen technologies and their main drivers. These strategies have been benchmarked against the Australia Council National Hydrogen Strategy and the Australia Electricity Market Operator Strategy regarding the scenario of a hydrogen superpower for Australia to become an essential player in the hydrogen market using the IBA (Interactive Bundle Analysis) framework.\u0000 The seven territories’ strategies were analyzed, and a set of recommendations are derived from this analysis with the aim to reinforce each territory strategy, providing the Australian Federal Government a framework to assess which project to finance projects first and assist in de-risking them to attract private capital, which is essential for the country to become a large-scale hydrogen producer and exporter.\u0000 This analysis recommends that should Australia focus on the development of blue hydrogen first and secures market share via Western Australia using steam methane reformer (SMR) and Victoria with the brown coal gasification, both fitted with the corresponding carbon capture and storage (CCS). In parallel, the Australian Federal government should incentivize Tasmania to produce green hydrogen followed by Queensland and Western Australia while other territories need to develop as per their individual strengths.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121206091","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}
Manojkumar Gudala, Zhen Xu, Zeeshan Tariq, B. Yan, Shuyu Sun
In this study we developed mathematical model for thermo-hydro-mechanical process occurs within the geothermal reservoir with variable rock/fracture/fluid parameters. The influence of fracture network on the cold plume movement, pore pressure, changes in the rock/fracture effective stress under the same operating conditions. The injected fluid transport to extraction well from injection well within the interconnected fractures. In the same direction variation of the effective stress, pore pressure both in rock matrix and fractures was observed. Due to the variation of effective stress in the fracture, it will undergo shearing and alter the fracture aperture. This variation of fracture aperture will create a micro-seismic moment in the fractured geothermal reservoir. The magnitude of micro-seismic moment and hyper center were changing with time and highly sensitive to the fracture connectivity of each fracture set. The developed mathematical model was observed these variations efficiently. Thus, the developed model can be utilized to address the variations occurred throughout the heat extraction in the fractured geothermal reservoir in conjunction with the activation of fracture and location of hyper center of each seismic moment.
{"title":"Numerical Investigations on Induced Seismicity and Fracture Activation in Fractured Geothermal Reservoirs","authors":"Manojkumar Gudala, Zhen Xu, Zeeshan Tariq, B. Yan, Shuyu Sun","doi":"10.2118/214418-ms","DOIUrl":"https://doi.org/10.2118/214418-ms","url":null,"abstract":"\u0000 In this study we developed mathematical model for thermo-hydro-mechanical process occurs within the geothermal reservoir with variable rock/fracture/fluid parameters. The influence of fracture network on the cold plume movement, pore pressure, changes in the rock/fracture effective stress under the same operating conditions. The injected fluid transport to extraction well from injection well within the interconnected fractures. In the same direction variation of the effective stress, pore pressure both in rock matrix and fractures was observed. Due to the variation of effective stress in the fracture, it will undergo shearing and alter the fracture aperture. This variation of fracture aperture will create a micro-seismic moment in the fractured geothermal reservoir. The magnitude of micro-seismic moment and hyper center were changing with time and highly sensitive to the fracture connectivity of each fracture set. The developed mathematical model was observed these variations efficiently. Thus, the developed model can be utilized to address the variations occurred throughout the heat extraction in the fractured geothermal reservoir in conjunction with the activation of fracture and location of hyper center of each seismic moment.","PeriodicalId":306106,"journal":{"name":"Day 4 Thu, June 08, 2023","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132419013","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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