Research progress and potential of new enhanced oil recovery methods in oilfield development

This paper reviews the basic research means for oilfield development and also the researches and tests of enhanced oil recovery(EOR)methods for mature oilfields and continental shale oil development,analyzes the problems of EOR methods,and proposes the relevant research prospects.The basic research means for oilfield development include in-situ acquisition of formation rock/fluid samples and non-destructive testing.The EOR methods for conventional and shale oil development are classified as improved water flooding(e.g.nano-water flooding),chemical flooding(e.g.low-concentration middle-phase micro-emulsion flooding),gas flooding(e.g.micro/nano bubble flooding),thermal recovery(e.g.air injection thermal-aided miscible flooding),and multi-cluster uniform fracturing/water-free fracturing,which are discussed in this paper for their mechanisms,approaches,and key technique researches and field tests.These methods have been studied with remarkable progress,and some achieved ideal results in field tests.Nonetheless,some problems still exist,such as inadequate research on mechanisms,imperfect matching technologies,and incomplete industrial chains.It is proposed to further strengthen the basic researches and expand the field tests,thereby driving the formation,promotion and application of new technologies.

Using a support vector machine method to predict the development indices of very high water cut oilfields

Because the oilfields in eastern China are in the very high water cut development stage, accurate forecast of oilfield development indices is important for exploiting the oilfields efficiently. Regarding the problems of the small number of samples collected for oilfield development indices, a new support vector regression prediction method for development indices is proposed in this paper. This method uses the principle of functional simulation to determine the input-output of a support vector machine prediction system based on historical oilfield development data. It chooses the kernel function of the support vector machine by analyzing time series characteristics of the development index; trains and tests the support vector machine network with historical data to construct the support vector regression prediction model of oilfield development indices; and predicts the development index. The case study shows that the proposed method is feasible, and predicted development indices agree well with the development performance of very high water cut oilfields.

The Application of Optimum Decision in Oilfield Development

The major steps of oilfield development are given in this paper. The optimal model of oilfield development is built and the methods of optimum decision analysis are studied. The solution and analysis of the optimal tactics have been set up according to the data collected in the oilfield.

Investigation of the influences of asphaltene deposition on oilfield development using reservoir simulation

This paper investigates the deposition of asphaltenes in the porous medium of the studied field in Russia and predicts production profiles based on uncertainty evaluation. This problem can be solved by dynamic modeling, during which production profiles are estimated in two scenarios: with and without the activation of the asphaltene option. Calculations are carried out for two development scenarios: field operation under natural depletion and water injection into the aquifer as a reservoir pressure maintenance system. A full-scale compositional reservoir simulation model of the Russian oilfield was created. Within a dynamic simulation, the asphaltene option was activated and the asphaltene behavior in oil and porous medium was tuned according to our own special laboratory experiments. The model was also matched to production historical data, and a pattern model was prepared using the full-scale simulation model. Technological and the asphaltene option parameters were used in sensitivity and an uncertainty evaluation. Furthermore, probable production profiles within a forecast period were estimated. The sensitivity analysis of the pattern model to input parameters of the asphaltene option allowed determining the following heavy-hitters on the objective function: the molar weight of dissolved asphaltenes as a function of pressure, the asphaltene dissociation rate, the asphaltene adsorption coefficient and the critical velocity of oil movement in the reservoir. Under the natural depletion scenario, our simulations show a significant decrease in reservoir pressure and the formation of drawdown cones leading to asphaltene deposition in the bottom-hole area of production wells, decreasing their productivity. Water injection generally allows us to significantly reduce the volume of asphaltene phase transitions and has a positive effect on cumulative oil production. Injecting water into aquifer can keep the formation pressure long above the pressure for asphaltene precipitation, preventing the asphaltene deposition resulted from interaction of oil and water, so this way has higher oil production.

Low cost development strategy for oilfields in China under low oil prices

By reviewing the challenges in the development of oilfields in China under low oil prices,this study analyzes the root causes of cost rising,put forwards the low cost oilfield development strategy and specific paths to realize the strategy,and predicts the development potential and prospect of oilfields in China.In addition to the low grade of the reservoir and high development maturation,the fundamental reasons of development full cost rising of oilfields in China are as follows:(1)Facing the problem of resources turning poorer in quality,we have built production capacity at a pace too fast before making enough technical and experimental preparation;(2)technical engineering service model leads to high service cost;(3)team of oil development expertise and matched engineering system cannot satisfy the technical requirements of stabilizing oil production,controlling water cut and fine development.To realize development at low cost,the core is to increase economic recoverable reserves.The concrete paths include:(1)to explore the"Daqing oilfield development culture",improve the ability of leaders in charge of development,and inspire potential of staff;(2)to improve the ability of reservoir dynamics control,and implement precise development by following scientific principles;(3)to speed up integration of water flooding and enhanced oil recovery(EOR)and technological upgrading in order to enhance oil recovery;(4)to innovate key techniques in gas flooding and accelerate the industrial popularization of gas flooding;(5)to break the related transaction barriers and create new management models;and(6)to collaboratively optimize strategic layout and cultivate key oil bases.Although oilfield development in China faces huge challenges in cost,the low-cost development strategy will succeed as long as strategic development of mature and new oil fields is well planned.The cores to lower cost are to control decline rate and enhance oil recovery in mature oil fields,and increase single well productivity through technical innovation and improve engineering service efficiency through management innovation in new oil fields.

Systematic improvement in Tong's B-type water drive method

Tong's B-type water drive method was proposed as early as the 1970s and has been widely applied in the dynamic prediction and effective evaluation of oilfield development.Through extensive applications and studies,many researchers found that the statistical constants in the formula of the Tong's B-type water drive method(also referred to as the Tong's B-type formula)are not applicable to multiple types of reservoirs,especially low-permeability ones,due to the limited range of reservoir types when the formula was conceived.Moreover,they put forward suggestions to improve the Tong's B-type formula,most of which focused on the research and calculation of the first constant in the formula.For oilfields in the development stages of high or ultra-high water cuts,it is widely accepted that different types of reservoirs have different limit water cuts.This understanding naturally makes it necessary to further modify the Tong's B-type formula.It is practically significant to establish the water drive formula and cross plot considering that the two constants in the formula vary with reservoir type.By analyzing the derivation process and conditions of the Tong's B-type formula,this study points out two key problems,i.e.,the two constants 7.5 and 1.69 in the formula are not applicable to all types of reservoir.Given this,this study establishes a function between key reservoir parameters and the first constant and another function between key reservoir parameters and recovery efficiency.Based on the established two functions and considering that different types of oil reservoir have different limit water cuts,this study develops an improved Tong's B-type formula and prepares the corresponding improved cross plot.The results of this study will improve the applicability and accuracy of Tong's B-type water drive method in predicting the trend of water cut increasing for different types of oil reservoirs.

Effective EOR Technique Developed in Henan Oilfield

ＥｆｆｅｃｔｉｖｅＥＯＲＴｅｃｈｎｉｑｕｅＤｅｖｅｌｏｐｅｄｉｎＨｅｎａｎＯｉｌｆｉｅｌｄＸｕＸｉａｏｂｉｎＣｈｉｎａｈａｓｍａｄｅｓｏｍｅｐｒｏｇｒｅｓｓｉｎｏｉｌｒｅｃｏｖｅｒｙｂｙｐｈｙｓｉｃａｌｍｅｔｈｏｄ．Ｉｎｔｒｏｄｕｃｉｎｇｔｅｃｈｎｏ...

JKR Involved in Developing Old Oilfields in Jilin

ＪＫＲＩｎｖｏｌｖｅｄｉｎＤｅｖｅｌｏｐｉｎｇＯｌｄＯｉｌｆｉｅｌｄｓｉｎＪｉｌｉｎＳｕｎＸｉａｎｓｈｅｎｇ，ＷａｎｇＫｅｙｕ（ＩｎｔｅｒｎａｔｉｏｎａｌＥｘｐｌｏｒａｔｉｏｎａｎｄＤｅｖｅｌｏｐｍｅｎｔＣｏｒｐｏｒａｔｉｏｎＢｕｒｅａｕｏｆＣＮＰＣ...

塔河奥陶系碳酸盐岩油藏缝洞系统发育模式与分布规律

塔河奥陶系碳酸盐岩缝洞型油藏是以缝洞为主要储集空间的特殊型油藏。区域构造演化与古岩溶发育关系密切,塔河地区奥陶系碳酸盐岩经历了加里东中期及海西早期岩溶作用,海西早期裸露风化壳岩溶作用是塔河岩溶储集体发育的主要因素。塔里木盆地北缘一间房、硫磺沟、三道班和五道班等地区奥陶系古岩溶露头地质调查及塔河油田储集体发育特征揭示该区奥陶系碳酸盐岩存在地下河系统型、岩溶洞穴型和溶蚀孔缝型3大类型的缝洞系统发育模式。地下河系统和岩溶洞穴是最主要的储集体类型。断裂带附近是缝洞系统发育的密集带;古地貌控制了缝洞系统的平面分布,岩溶台地内的峰丛洼地区溶洞最发育,其次以岩溶缓坡内的丘峰洼地区和丘丛垄脊槽谷区古岩溶缝洞系统发育程度高;垂向上溶洞发育具有明显分带性,表层岩溶带是最重要的岩溶发育段。

The optimal model of oilfield development investment based on Data Envelopment Analysis

The investment problem of oilfield development is to trade off the investment exploration investment and development investment.With low return on investment got by using the existing method to solve this problem,we construct an optimal model to improve it based on Data Envelopment Analysis(DEA)method and the relations about investment and proven reserves,investment and output as well as production cost.Data Envelopment Analysis(DEA)method is used to present a method to determine the optimal scale of productivity construction investment in unit production.The relation between total cumulated proven reserves and cumulative exploration investment is denoted as an exponential model.The relation among productions and remaining recoverable reserves as well as production cost may be described as an exponential operational cost function.Based on above two relation models and investment effectiveness coefficients of every block,we establish an optimal model whose objective function is net present value(NPV)profit maximum,whose constrain conditions include investment,reserve/production ratio,production and some equality constraints under the mode of sustainable development.It can be solved by genetic algorithms.The result of case study shows that this optimal investment of oilfield development has multi-stage investment structure under given conditions;the model can provide scientific basic theory for oil companies to make a long-term strategic program and investment plan in oil exploration and development,may decrease the subjective blindness in the investment and bring about a reasonable and orderly exploration and development of oil resources.

A compositional function hybridization of PSO and GWO for solving well placement optimisation problem

Advances in technology and optimisation are helping to improve decision making in the oil and gas industry.However,most of the traditional metaheuristic algorithms applied in well placement optimisation problems suffer from extensive parameter experimentations and local optimum trapping issues.This couples with the complex and heterogeneous nature of hydrocarbon reservoirs and increased decision variables poses severe simulation process demands.This study considered a functional composition integration approach to formulate a robust hybrid metaheuristic algorithm called HGWO-PSO.The HGWO-PSO leverages on the strengths of Grey Wolf Optimiser(GWO)and Particle Swarm Optimisation(PSO)and the Clerc's parameter setting considerations.A rigorous approach which enforces regulatory agreed minimum well spacing was incorporated in the optimisation process.Reservoir models ranging from unimodal to multimodal spatial systems were used as examples to test the explorative and exploitative capabilities of the algorithms.In this paper we show the performance curve and statistical analysis of HGWO-PSO as a well placement algorithm and compares its performance with that of standalone PSO,and GWO and the traditional Genetic Algorithm(GA).Results revealed that the HGWO-PSO demonstrated comparative performances in terms of exploration and exploitation obtaining the best optimal solutions which give highest contractor's NPVs in majority of cases considered.Again,the means and standard deviations for HGWO-PSO among the various runs showed consistent and efficient performance.The Wilcoxon signed rank test conducted gave very low p-values suggesting uniqueness of HGWO-PSO from the other metaheuristic variants.Additionally,the computational speed of HGWO-PSO was relatively better as compared to the individual GWO and PSO in most the test cases.The simulation results for all test cases confirm that implementation of HGWO-PSO can cause considerable improvement in locations of wells even in heterogeneous reservoirs.