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Machine learning methods for predicting CO_(2) solubility in hydrocarbons

Petroleum Science 2024年第5期21卷 3340-3349页

作者： Yi Yang binshan ju Guangzhong Lü Yingsong Huang School of Energy Resources China University of Geosciences(Beijing)Beijing100083China Key Laboratory of Marine Reservoir Evolution and Hydrocarbon Enrichment Mechanism Ministry of EducationBeijing100083China Key Laboratory of Geological Evaluation and Development Engineering of Unconventional Natural Gas Energy Beijing100083China Shengli Oilfield Company SINOPECDongying257015ShandongChina

The application of carbon dioxide(CO_(2)) in enhanced oil recovery(EOR) has increased significantly, in which CO_(2) solubility in oil is a key parameter in predicting CO_(2) flooding performance. Hydrocarbons are the major constituents of oil, thus the focus of this work lies in investigating the solubility of CO_(2) in hydrocarbons. However, current experimental measurements are time-consuming, and equations of state can be computationally complex. To address these challenges, we developed an artificial intelligence-based model to predict the solubility of CO_(2) in hydrocarbons under varying conditions of temperature, pressure, molecular weight, and density. Using experimental data from previous studies,we trained and predicted the solubility using four machine learning models: support vector regression(SVR), extreme gradient boosting(XGBoost), random forest(RF), and multilayer perceptron(MLP).Among four models, the XGBoost model has the best predictive performance, with an R^(2) of ***, sensitivity analysis and evaluation of the relative impacts of each input parameter indicate that the prediction of CO_(2) solubility in hydrocarbons is most sensitive to pressure. Furthermore, our trained model was compared with existing models, demonstrating higher accuracy and applicability of our model. The developed machine learning-based model provides a more efficient and accurate approach for predicting CO_(2) solubility in hydrocarbons, which may contribute to the advancement of CO_(2)-related applications in the petroleum industry.

关键词： CO_(2)solubility Machine learning Support vector regression Extreme gradient boosting Random forest Multi-layer perceptron

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Modeling CO_2 miscible flooding for enhanced oil recovery

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Petroleum Science 2012年第2期9卷 192-198页

作者： ju binshan Wu Yu-Shu Qin Jishun Fan Tailiang Li Zhiping School of Energy Resources China University of Geosciences(Beijing)Beijing100083China Key Laboratory of Marine Reservoir Evolution and Hydrocarbon Accumulation Mechanism Ministry of EducationChinaUniversity of Geosciences(Beijing)Beijing 100083China Colorado School of Mines USA PetroChina Research Institute of Petroleum Exploration and Development Beijing 100083China

The injection of fuel-generated CO2 into oil reservoirs will lead to two benefits in both enhanced oil recovery （EOR） and the reduction in atmospheric emission of CO2. To get an insight into CO2 miscible flooding performance in oil reservoirs, a multi-compositional non-isothermal CO2 miscible flooding mathematical model is developed. The convection and diffusion of CO2-hydrocarbon mixtures in multiphase fluids in reservoirs, mass transfer between CO2 and crude, and formation damages caused by asphaltene precipitation are fully considered in the model. The governing equations are discretized in space using the integral finite difference method. The Newton-Raphson iterative technique was used to solve the nonlinear equation systems of mass and energy conservation. A numerical simulator, in which regular grids and irregular grids are optional, was developed for predicting CO2 miscible flooding processes. Two examples of one-dimensional （1D） regular and three-dimensional （3D） rectangle and polygonal grids are designed to demonstrate the functions of the simulator. Experimental data validate the developed simulator by comparison with 1D simulation results. The applications of the simulator indicate that it is feasible for predicting CO2 flooding in oil reservoirs for EOR.

关键词： Compositional simulator CO2 flooding mathematical model irregular grids

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A tight sandstone multi-physical hydraulic fractures simulator study and its field application

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Petroleum 2020年第2期6卷 198-205页

作者： Yonghong Wang binshan ju Shihao Wang Zhenzhou Yang Qing Liu School of Energy Resource China University of GeoscienceBeijingChina CNPC Engineering Technology R&D Company Limited(CPET) China Petroleum Engineering Department Colorado School of MinesGoldenCO80401USA

During the past years,the recovery of unconventional gas formation has attracted lots of attention and achieved huge *** produce gas from the low-permeability unconventional formations,hydraulic fracturing technology is essential and *** this paper,we present the development of a three-dimensional thermalhydraulic-mechanical numerical simulator for the simulation of hydraulic fracturing operations in tight sandstone *** simulator is based on integrated finite difference(IFD)*** this method,the simulation domain is subdivided into sub domains and the governing equations are integrated over a sub domain with flux terms expressed as an integral over the sub domain boundary using the divergence *** simulator conducts coupled thermal-hydraulic-mechanical simulation of the initiation and extension of hydraulic *** also calculates the mass/heat transport of injected hydraulic fluids as well as *** simulator is able to handle anisotropic formations with multiple *** simulator has been validated by comparing with an analytical solution as well as Ribeiro and Sharma *** model can simulate fracture spacing effect on fracture profile when combining IFD with Discontinuous Displacement Method(DDM).

关键词： Tight sandstone Hydraulic fracture simulator Integrated finite difference discretization Stress contrast

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A novel numerical simulation of CO_(2) immiscible flooding coupled with viscosity and starting pressure gradient modeling in ultra-low permeability reservoir

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Frontiers of Earth Science 2023年第3期17卷 884-898页

作者： Jie CHI binshan ju Jiabei WANG Xing ZHANG Wenbin CHEN Mengfei ZHANG School of Big Data and Fundamental Sciences Shandong Institute of Petroleum and Chemical TechnologyDongying 257061China School of Energy Resources China University of Geosciences(Beijing)Beijing 100083China Key Laboratory of Geological Evaluation and Development Engineering of Unconventional Natural Gas Energy Beijing 100083China School of Petroleum Engineering Chongqing University of Science&TechnologyChongqing 401331China Research Institute of Petroleum Engineering Technology Shengli Oilfield CompanySINOPECDongying 257000China

CO_(2) immiscible flooding is an environmentally-friendly and effective method to enhance oil recovery in ultra-low permeability reservoirs.A mathematical model of CO_(2) immiscible flooding was developed,considering the variation in crude oil viscosity and starting pressure gradient in ultra-low permeability reservoirs based on the non-Darcy percolation *** mathematical model and numerical simulator were developed in the C++language to simulate the effects of fluid viscosity,starting pressure gradient,and other physical parameters on the distribution of the oil pressure field,oil saturation field,gas saturation field,oil viscosity field,and oil *** results showed that the formation pressure and pressure propagation velocity in CO_(2) immiscible flooding were lower than the findings without considering the starting pressure *** formation oil content saturation and the crude oil formation viscosity were higher after the consideration of the starting pressure *** viscosity of crude oil considering the initiation pressure gradient during the formation was higher than that without this gradient,but the yield was lower than that *** novel mathematical models helped the characterization of seepage resistance,revealed the influence of fluid property changes on seepage,improved the mathematical model of oil seepage in immiscible flooding processes,and guided the improvement of crude oil recovery in immiscible flooding processes.

关键词： viscosity starting pressure gradient flow simulation CO_(2)immiscible flooding ultra-low permeability reservoir

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ENHANCED OIL RECOVERY BY FLOODING WITH HYDROPHILIC NANOPARTICLES

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China Particuology 2006年第1期4卷 41-46页

作者： binshan ju Tailiang Fan Mingxue Ma School of Energy Resource China University of Geosciences Beijing 100083 P. R. China Weff-Log Research Center of Shengli Off-Field Dongying 257095 P. R. China

In this paper, the mechanism of enhanced oil recovery using lipophobic and hydrophilic polysilicon （LHP） nanoparticles ranging in size from 10 to 500 nm for changing the wettability of porous media was analysed theoretically. A one-dimensional two-phase mathematical model considering the migration and adsorption of LHP and wettability change in reservoir rock was proposed, and a simulator was developed to quantitatively predict the changes in relative and effective permeability of the oil and water phases and the oil recovery in sandstone after water driving. Numerical simulations were conducted to study the distribution of the particle concentration, the reduction in porosity and absolute permeability, the LHP volume retention on pore walls and in pore throats along a dimensionless distance, and oil production performance. In conclusion, oil recovery can obviously be improved by flooding with hydrophilic nanometer powders though permeability declines for the retention of nanoparticles in porous media. It is suggested that an LHP concentration ranging from 0.02 to 0.03 is preferable to enhance oil recovery.

关键词： nanoparticle wettability change porous media enhance oil recovery mathematical model

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Laboratory simulation of CO_(2) immiscible gas flooding and characterization of seepage resistance

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Frontiers of Earth Science 2023年第3期17卷 797-817页

作者： Jie CHI binshan ju Wenbin CHEN Mengfei ZHANG Rui ZHANG Anqi MIAO Dayan WANG Fengyun CUI School of Big Data and Fundamental Sciences Shandong Institute of Petroleum and Chemical TechnologyDongying 257061China School of Energy Resources China University of Geosciences(Beijing)Beijing 100083China Key Laboratory of Geological Evaluation and Development Engineering of Unconventional Natural Gas Energy Beijing 100083China School of Chemical Engineering Shandong Institute of Petroleum and Chemical TechnologyDongying 257061China

CO_(2) flooding can significantly improve the recovery rate, effectively recover crude oil, and has the advantages of energy saving and emission reduction. At present, most domestic researches on CO_(2) flooding seepage experiments are field tests in actual reservoirs or simulations with reservoir numerical simulators. Although targeted, the promotion is poor. For the characterization of seepage resistance, there are few studies on the variation law of seepage resistance caused by the combined action in the reservoir. To solve this problem, based on the mechanism of CO_(2), a physical simulation experiment device for CO_(2) non-miscible flooding production manner is designed. The device adopts two displacement schemes, gas-displacing water and gas-displacing oil, it mainly studies the immiscible gas flooding mechanism and oil displacement characteristics based on factors such as formation dip angle, gas injection position, and gas injection rate. It can provide a more accurate development simulation for the actual field application. By studying the variation law of crude oil viscosity and start-up pressure gradient, the characterization method of seepage resistance gradient affected by these two factors in the seepage process is proposed. The field test is carried out for the natural core of the S oilfield, and the seepage resistance is described more accurately. The results show that the advancing front of the gas drive is an arc, and the advancing speed of the gas drive oil front is slower than that of gas drive water;the greater the dip angle, the higher the displacement efficiency;the higher the gas injection rate is, the higher the early recovery rate is, and the lower the later recovery rate is;oil displacement efficiency is lower than water displacement efficiency;taking the actual core of S oilfield as an example, the mathematical representation method of core start-up pressure gradient in low permeability reservoir is established.

关键词： laboratory_simulation viscosity starting pressure gradient CO immiscible flooding characterization of seepage resistance

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页岩甲烷高压等温吸附模型评价与改进

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煤炭学报 2020年第9期45卷 3208-3218页

作者：董银涛鞠斌山刘楠楠中国地质大学(北京)能源学院北京100083 非常规天然气地质评价与开发工程北京市重点实验室北京100083 中国地质大学(北京)煤层气开发利用国家工程研究中心煤储层物性实验室北京100083 中海油研究总院北京100028

为确定合理的页岩甲烷高压等温吸附模型,以准确拟合实测过剩吸附量曲线,并计算其绝对吸附量曲线。选取常用的8种吸附公式及3种吸附相密度计算方法,分别组成高压等温吸附模型,并以过剩吸附量的拟合度R2、绝对吸附量校正的合理性、吸附相... 详细信息

为确定合理的页岩甲烷高压等温吸附模型,以准确拟合实测过剩吸附量曲线,并计算其绝对吸附量曲线。选取常用的8种吸附公式及3种吸附相密度计算方法,分别组成高压等温吸附模型,并以过剩吸附量的拟合度R2、绝对吸附量校正的合理性、吸附相密度计算的合理性以及吸附理论选择的合理性为考核指标,分别采用333与363 K温度条件下共18组实测值对其进行定量评价。推导了吸附相密度关于压力与温度的函数,并组合使用Langmuir-Freundlich与Dubinin-Radushkevich吸附公式,构建了改进的高压等温吸附模型。结果表明:在3种吸附相密度计算方法中,拟合吸附相密度法最佳,该方法结合Langmuir-Freundlich或Dubinin-Radushkevich吸附公式构成的吸附模型最准确,其拟合过剩吸附量的R2平均值分别为0.9983和0.9978;给定吸附相密度法构成的吸附模型对过剩吸附量的拟合度较低;而过剩吸附量与气体密度曲线计算吸附相密度法的准确性较差。改进模型对18组实测过剩吸附量的拟合度R2平均值为0.9969;计算绝对吸附量的偏差为0.087,优于现有模型;且其具有物理基础,符合页岩甲烷吸附机理。

关键词：页岩气高压等温吸附过剩吸附吸附模型

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煤层气直井井筒环空压力模型

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煤炭学报 2018年第9期43卷 2534-2542页

作者：董银涛鞠斌山张遂安中国地质大学(北京)能源学院北京100083 非常规天然气地质评价与开发工程北京市重点实验室北京100083 中国地质大学(北京)煤层气开发利用国家工程研究中心北京100083 中国石油大学(北京)煤层气研究中心北京102249

为实现煤层气直井排采各阶段井筒环空压力分布的计算,为煤层气井的控压排采提供指导。结合国内煤层气井的生产实际,研究了以油管排水、环空产气为生产方式的煤层气直井,在排采各阶段的井筒内流体分布状态。提出了环空内的纯液流仅出现... 详细信息

为实现煤层气直井排采各阶段井筒环空压力分布的计算,为煤层气井的控压排采提供指导。结合国内煤层气井的生产实际,研究了以油管排水、环空产气为生产方式的煤层气直井,在排采各阶段的井筒内流体分布状态。提出了环空内的纯液流仅出现于煤层气解吸产出前;气液两相流阶段的环空内仅产生泡状流与段塞流;环空内气体上升不携液。基于此,采用水动力学方法,建立了3个井筒环空压力模型,分别为环空液体单相压力模型、环空气液两相压力模型以及环空气体单相压力模型,并给出了模型间的过渡条件及模型求解步骤,从而实现煤层气直井排采各阶段的环空压力分布计算。经41口井、共71组实测数据验证,所建立的3个环空压力模型,其计算结果与实测值的平均误差依次为:2. 70%,7. 96%及3. 80%,对煤层气直井井筒环空压力的计算具有一定准确性与实用性。

关键词：煤层气直井井筒环空压力模型气液流动

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裂缝性油藏二氧化碳驱的多组分数值计算模型

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西南石油大学学报（自然科学版） 2015年第2期37卷 93-100页

作者：邸元吴玉树鞠斌山北京大学工学院北京海淀100871 美国科罗拉多矿业大学石油工程系科罗拉多高登80401 中国地质大学(北京)能源学院北京海淀100083

对于预测油藏二氧化碳驱的效果,黑油模型不再适用,必须采用组分模型。研究了裂缝性油藏二氧化碳驱的三相多组分数值计算模型,给出了相关的计算方法和公式。采用多重连续介质理论来模拟裂缝性油藏中的输运过程,每个组分的质量传输包括传... 详细信息

对于预测油藏二氧化碳驱的效果,黑油模型不再适用,必须采用组分模型。研究了裂缝性油藏二氧化碳驱的三相多组分数值计算模型,给出了相关的计算方法和公式。采用多重连续介质理论来模拟裂缝性油藏中的输运过程,每个组分的质量传输包括传导和扩散过程。多相流体的流动采用Darcy定律来描述;组分的扩散采用Fick定律来描述。二氧化碳在岩石颗粒上的吸附及油相重组分在岩石骨架上的沉淀采用非线性等温吸附来描述。用串状毛管模型来考虑沥青质沉积对储层渗透率的影响。采用积分差分法对各组分的质量守恒方程进行空间离散,并按全隐式格式通过Newton迭代法进行求解。根据Soave-Redlich-Kwong状态方程计算流体的物性。对于油–水–气(二氧化碳)三相的相平衡计算,分别给出了平衡常数法、闪蒸计算法和最小Gibbs自由能法的计算公式。

关键词：数值模拟组分模型二氧化碳驱裂缝性油藏相平衡

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水驱油藏优势渗流通道识别及其效果分析

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现代地质 2024年第6期38卷 1523-1531页

作者：张庆宇鞠斌山中国地质大学(北京)能源学院北京100083 非常规天然气能源地质评价与开发工程重点实验室北京100083

油藏中优势渗流通道的存在及其分布,显著影响着油藏开发对策与开发效果。本文综合运用多相渗流和储层地质理论,建立表征注采井间小层连通性及识别优势渗流通道存在的方法。基于小层对比法、地质建模法和示踪剂法,详细解剖某油田一个代... 详细信息

油藏中优势渗流通道的存在及其分布,显著影响着油藏开发对策与开发效果。本文综合运用多相渗流和储层地质理论,建立表征注采井间小层连通性及识别优势渗流通道存在的方法。基于小层对比法、地质建模法和示踪剂法,详细解剖某油田一个代表性井组的砂体连通性和优势渗流通道的发育特征。研究结果表明:在研究区实例井组的注采井间,三种方法得到的储层连通率差异较大,其中精度较高的示踪剂法确定的连通率为40%;并在重点解剖小层中识别出三条优势渗流通道,依据示踪剂见剂速度与回采率,对三条优势渗流通道的发育程度进行了分级。对比实际监测结果,小层对比分析法得到的连通率明显偏高,地质建模法与示踪剂法得到的连通率比较接近,两种方法得到的连通率均受到开发小层的储层沉积与相变规律、非均质性及实测资料精细度的影响。示踪剂法识别优势渗流通道效果最佳,比地质建模法的识别精度提高了25%。

关键词：优势渗流通道井间连通性示踪剂小层对比油藏建模

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