Influence of the objective function in the history matching process

An assisted history matching process always requires two distinct parts: a parameterization to select the uncertain attributes of the model and an automatic procedure that minimizes the distance between the observed production and the simulation model curves. The focus of this work is the second part, where an objective function is necessary to represent mathematically the quality of the model. However, due to the complexity of the models, this function is frequently a combination of several functions that represent the quality of the match in several wells and less attention is given to the influence of the objective function in the optimization process. This paper proposes a study to show the influence of a global objective function on the history matching process using a synthetic reservoir model with 20 uncertain attributes. Results of the quality matching index of eight different global objective functions are compared at the end of the process. The optimized simulation models, generated by the optimization phase with different global objective functions, are compared with the base model and production history.     

Surrogate-based Optimization of Horizontal Well Placement in a Mature Oil Reservoir

Abstract

Exploitation of mature oil reservoirs has forced researchers to find ways for enhancing production from such reservoirs. An effective way to do so is drilling horizontal wells. There are many advantages for these kinds of wells but they require extra investment for drilling and completion. The objective of this research is to choose location, direction, and length of a new horizontal well to maximize accumulative oil production over a planning horizon. The authors employ various metamodeling techniques in order to build a good approximate model for estimation of accumulated outflow from each well scenario. This leads to a significant reduction in the computation time. The authors built and compared 18 metamodels based on quadratic, multiplicative, and radial basis functions for the reservoir under study. Then, the best model was introduced to a global optimization search using a Genetic algorithm. Numerical results showed that 3 million barrels of more oil could be produced from the designated well as compared with those of the initial scenarios, which is a significant improvement.     

油藏数值模拟自动历史拟合方法——以Nelson油田为例

针对北海中部Nelson油田,研究油藏数值模拟自动历史拟合方法。完整的油藏自动历史拟合工作流程包括选择要调整的油藏变量、选择参数调整方法、自动历史拟合、数据分析、组合最优结果得到最优的油藏模型集5个步骤。以净毛比、水平渗透率、垂直渗透率为调整参数,采用全局单变量法、区域多变量法、局部多变量法等3种油藏参数调整方法,并结合生产数据和时移地震数据,对Nelson油田进行自动历史拟合。结果表明,局部参数调整方法减少了模拟中模型的数目和计算时间,提高了模拟精度,使得油藏中油水产量拟合误差大大降低,在Nelson油田应用效果最好。全局单变量法适合于历史拟合参数相互独立的情况;对于井网密度大且井间关联性强、历史拟合参数相互影响的油藏,最好选用区域多变量法进行参数调整;对于油藏历史拟合参数相互影响但每个选定调整区域相互独立的油藏,局部多变量法更加适用。     

Application of Horizontal Wells to Improve Injectivity During Polymer Flood Processes

Abstract

This numerical study was undertaken to investigate and compare the performances of polymer flood processes through horizontal or vertical wells. To achieve the objective, the author performed an extensive numerical simulation for 3 different well configurations under polymer flood followed by waterflood. The potential for a horizontal well application was assessed through different scenarios in combinations of injection and production wells and reservoir geometry. Other parameters included the length and spacing of horizontal injectors and horizontal or vertical producers. For different parameters of the system, performances were compared in terms of cumulative recovery and water-oil ratio at the production well and pressure drop or injectivity at the injection well. Results demonstrate that additional oil can be recovered and injectivity was significantly improved by utilizing a combination of horizontal wells when the same volume of fluid is injected into the reservoir. The improvement of injectivity through a horizontal injection well was higher when it was combined with a horizontal producer. Parameters such as reservoir thickness, well spacing, and well length are also shown to impact the predicted injectivity. Improvement in injectivity is obtained for thicker and larger reservoirs and longer horizontal wells.     

Average reservoir pressure determination for homogeneous and naturally fractured formations from multi-rate testing with the TDS technique

Average reservoir pressure is an important parameter which is utilized in almost all reservoir and production engineering studies. It also plays a relevant role in the majority of well intervention jobs, field appraisal, well sizing and equipment and surface facilities design.The estimation of the average reservoir pressure is normally obtained from buildup tests. However, it has a tremendous economic impact caused by shutting-in the well during the entire test. Since buildup tests are the most particular case of multi-rate tests, these are also used for estimation of the average reservoir pressure. Among them, two-rate tests present drawbacks because it is operationally difficult to keep constant the flow rates. Conventional methods for determination of the average reservoir pressure can be readily extended to multi-rate tests once the rigorous time is converted to equivalent time by time superposition.In this article a new, easy and practical methodology is presented for the determination of the average pressure in both homogeneous and naturally fractured reservoirs from multi-rate tests conducted in vertical oil wells located inside a close drainage region. The methodology which follows the philosophy of the TDS technique uses a normalized pressure and pressure derivative point found on any arbitrary point during the pseudosteady-state flow regime to readily provide the average reservoir pressure value.For verification of the effectiveness of the proposed solution, several field and simulated examples were worked out. We found that the average reservoir pressure results obtained from the proposed methodology match very well with those estimated from either conventional techniques or simulations.     

The Optimization of Underground Gas Storage in a Partially Depleted Gas Reservoir

Abstract

Underground gas storage (UGS) is a well-known technology to supply variable demand of natural gas market. The objective of this work is to demonstrate the feasibility of UGS development in an Iranian depleted fractured gas reservoir. For this purpose, gas demand analysis was conducted based on yearly consumption, and the peak condition demand was obtained. Then, a full-field multicomponent reservoir model was constructed based on the rock and fluid data and comprehensive production history. A modified Peng-Robinson equation was used to estimate the phase behavior of the reservoir and injection fluid. The compositional model was verified through performing history matching on gas production rate.

After history matching, an injection/withdrawal (I/W) schedule was designed to meet necessary gas consumption. Production scenarios were conducted to obtain optimum operating conditions for this reservoir. It was determined that at least four new wells are required to establish successful UGS plan to meet the target withdrawal rate. Results show that the use of a horizontal well is superior to a vertical well because of less water production during storage cycles. Water cut, productivity, and injectivity indexes of individual wells were considered as prominent factors to find the optimum well pattern, using a connection transmissibility factor to compare the capacity of each well to produce. In addition to constant I/W rate, a variable I/W rate scenario was proposed whose result showed no difference compare to the results obtained in previous runs.

Results show that the reservoir under study is capable of providing peak gas consumption during the cold months in Iran.     

Streamline-Based History Matching Constrained to Reservoir Geostatistics Using Gradual Deformation Technique

Abstract

A new and general procedure for history matching that uses streamline simulation and a gradual deformation technique has been proposed. Streamline trajectories define the major flow paths and help the algorithm to modify the reservoir model only in the regions that cause the mismatch between simulation results and field observations. The use of a gradual deformation technique enables the algorithm to remain constrained to reservoir geostatistics. It also reduces the number of independent variables in the optimization problem. In our algorithm, effective conductivities are defined along each streamline. The effective streamline conductivities are then adjusted using the values of measured and computed breakthrough times of individual streamlines. Then an intermediate objective function is defined to minimize the difference between adjusted (desired) and computed effective streamline conductivities. The algorithm continues until a satisfactory match is obtained. In order to examine the quality of our history matching procedure, it is applied to a synthetic reservoir.     

Computational Techniques for Closed–loop Reservoir Modeling with Application to a Realistic Reservoir

Abstract

Real-time model-based reservoir management requires efficient computational techniques for optimizing reservoir performance under uncertainty. A variety of algorithms addressing various aspects of this “closed-loop” methodology have been presented by various investigators, but substantial effort is still needed to make the entire process robust and efficient. In our recent work, we introduced an approximate feasible direction optimization algorithm for treating nonlinear path constraints (which are constraints such as maximum liquid production rate, which must be satisfied at every time step) and a new parameterization based on kernel principal component analysis (KPCA) for multipoint geostatistical models. The KPCA representation allows for the use of a gradient-based history-matching procedure that is able to maintain a higher degree of geological realism in the history-matched model. In this article, we combine these procedures with our general adjoint-based optimization technique to provide a full closed-loop capability. This integrated set of algorithms is then applied to a realistic field case. Specifically, we describe the key computational procedures and highlight the linkages required to provide the closed-loop capability. The example case considered is based on a Gulf of Mexico reservoir and involves three injection wells and four production wells operating under bottom hole pressure, total injection rate, and maximum water cut constraints. For this case, it is demonstrated that application of the closed-loop methodology provides a 25% increase in the net present value (NPV) over predictions for a realistic base case. This improvement is almost the same as that achieved using an open-loop approach, which is an idealized formulation in which the geological model is assumed to be known. These results demonstrate that the overall closed-loop procedure will indeed be applicable for practical cases with uncertain geology.     

Estimation of the Reservoir Permeability by Petrophysical Information Using Intelligent Systems

Abstract

Permeability is one of the most important parameters in order to evaluate a hydrocarbon reservoir. The permeability of a formation is usually determined from the cores and/or well tests. It should be noted that cores and well test data are often only available from few wells in a reservoir while the logs are available from the majority of the wells. Therefore, the evaluation of permeability from well log data represents a significant technical as well as economic advantage. Many fundamental problems remain unsolved by most predictive models. This article introduces the use of an improved neural network trained by a back propagation learning algorithm to provide solution for the permeability prediction from well log data. An Iranian offshore gas field which is located in the Persian Gulf, has been selected as the study area in this article. Well log data are available on a substantial number of wells. Core samples are also available from a few wells. It was shown that the neural network system is the most effective method in predicting permeability from well logs.     

The Decreasing Production Pattern for an Oilfield—Illustrated by the Dawanqi Oilfield

Abstract

Three methods are applied to study the decreasing production pattern of a complex sandstone reservoir with rolling exploitation and its annual output is ever increasing. Illustrated by Dawanqi Oilfield, the method of moving the start date of all producing wells to the same month has proved to be successful. This proposed method can also be used to study other sandstone reservoirs with similar situations.     

Optimizing the performance of smart wells in complex reservoirs using continuously updated geological models

Optimizing the operation of smart wells (i.e., wells with downhole chokes and sensors) remains a challenge, particularly in light of geological uncertainty. In this paper a combined valve optimization and history-matching procedure is presented and applied. The overall approach allows for the continuous updating of the geological model using data inferred from downhole sensors. The method uses numerically computed gradients, generated using a commercial reservoir simulator for function evaluations, for the valve optimization in conjunction with a probability perturbation approach for the history matching. The methodology is applied to three examples involving both variogram and multiple point geostatistical models. For these cases, using the proposed methodology, oil production is shown to be nearly equal to that achieved using optimized valves with known geology, indicating the potential benefits of the overall approach. In one of the cases, optimization over multiple history-matched models provides significant improvement over optimizing with a single model.     

建南气田低压低渗碳酸盐岩气藏储层改造技术

为了更好地开发鄂西地区建南碳酸盐岩气藏,通过三年的技术攻关,研究了一套低压低渗碳酸盐岩气藏的改造技术。在水平井上,实施屏蔽暂堵钻井、氧化解堵和水平井段酸压;在储层深部改造技术方面,进行了酸化、胶凝酸深部酸压和水力加砂压裂措施,并成功应用了2井次压裂、酸压复合工艺。同时还研究了3种配套的酸压措施管柱。     

蒸汽吞吐后转降黏化学驱加密井井位优化方法

稠油油藏在高轮次蒸汽吞吐后转入降黏化学驱是实现稳产的有效接替生产方式,根据稠油油藏蒸汽吞吐后转降黏化学驱井网加密的需要,以各注入井到生产井的拟见水时间趋于一致为目标,建立了加密井井位优化方法。针对蒸汽吞吐后地层中的含水饱和度分布不均匀问题,在Buckley-Leverett方程的右端项引入了注降黏剂开始时含水饱和度的等效注入量,并考虑降黏化学驱过程中原油黏度时变特征,建立了拟见水时间计算模型,采用时间迭代求解得到拟见水时间;以各注入井到生产井的拟见水时间的方差为目标函数,建立了加密井井位优化模型,采用粒子群算法对加密井井位优化模型进行求解。通过数值模拟验证了加密井井位优化方法的准确性,该研究成果对稠油油藏转降黏化学驱合理部署井网提供了技术支撑。     

蒸汽吞吐后转降黏化学驱加密井井位优化方法

稠油油藏在高轮次蒸汽吞吐后转入降黏化学驱是实现稳产的有效接替生产方式,根据稠油油藏蒸汽吞吐后转降黏化学驱井网加密的需要,以各注入井到生产井的拟见水时间趋于一致为目标,建立了加密井井位优化方法。针对蒸汽吞吐后地层中的含水饱和度分布不均匀问题,在Buckley-Leverett方程的右端项引入了注降黏剂开始时含水饱和度的等效注入量,并考虑降黏化学驱过程中原油黏度时变特征,建立了拟见水时间计算模型,采用时间迭代求解得到拟见水时间;以各注入井到生产井的拟见水时间的方差为目标函数,建立了加密井井位优化模型,采用粒子群算法对加密井井位优化模型进行求解。通过数值模拟验证了加密井井位优化方法的准确性,该研究成果对稠油油藏转降黏化学驱合理部署井网提供了技术支撑。     

底水油藏水平井水淹动态和水淹模式研究

不同水平井的水淹动态特征存在显着差异,而油藏类型、储层物性、流体性质、水平段长度、水平段位置和开发方式等因素都会对水平井水淹动态产生重要影响。以塔里木油田TZ402CⅢ油组水平井为例,根据其生产动态和历史拟合数值模拟,分析了水平井水淹动态特征差异及其影响因素,提出了塔里木油田底水油藏水平井的3种水淹模式,即线状见水整体水淹模式、点状见水整体水淹模式和点状见水局部水淹模式。可为水平井新井设计、完井方式选择、后期措施工艺选井等提供参考依据。     

The Relationship Between the Productivity Index and the Diffusivity Coefficient and Its Application in Reservoir Characterization

Abstract

The authors offer a reliable means to determine the diffusivity coefficient and permeability distribution throughout a reservoir while minimizing the number of expensive well tests. To explain this inexpensive procedure, data of the Asmari Reservoir—located in Iran on the Coast of Persian Gulf—are used. Using well test, petrophysical, pressure-volume-temperature, and production data, a relationship between the productivity index and the diffusivity coefficient is established for the Asmari Reservoir without relying on the reservoir radius value, which is uncertain when obtained from drawdown well testing. This method determines the optimum locations for new wells in development of giant fields.     

PRODUCTION SYSTEM MODELLING,CALIBRATION AND OPTIMIZATION IN PRACTICE

ABSTRACT

The present work reports on the application and development of a field planning methodology for an oil production station. NETOPT, which is a network optimizer based on a non-linear sequential quadratic programming, is used in this study. The report discusses this novel approach that considers the simultaneous hydraulic interaction of all individual wells and addresses the methodology used to implement a production system-modeling tool. Factors influencing network behavior are identified and discussed. Constrained and unconstrained optimization of oil/gross liquid production is conducted with decision variables based on gas-lift allocation and chokes openings. It was observed that the unconstrained model using injected gas rates to gas-lifted wells as decision variables improves the net oil production by approximately 6406 bbl/day, which represents an increase of 1.57% over the base case results. Specific problems were encountered during calibration of the production model and these are discussed with the lessons learned.     

A Weighted Ensemble Kalman Filter for Automatic History Matching

Abstract

The ensemble Kalman filter (EnKF) performs the initial sampling, forecasting, and assimilation steps for automatic history matching in the petroleum industry. It tunes multiple members sequentially and updates the statistical mean and variance of the model. Many applications have been reported in various publications. The forecasting step is implemented by running the reservoir model simulator. In the assimilation equation, the ensemble mean is calculated through equally weighting all the members. Therefore, the contribution factor to the mean from each member is the same. This paper proposes a modified assimilation equation by introducing a weighting factor for each ensemble member. Both the proposed weighted EnKF and the traditional EnKF are applied to a modified field case of a complex seventeen-layer reservoir. The performances of the weighted EnKF on production history match, forecasting, and field permeability match are better than those from the traditional EnKF. In addition, we investigate the impact of geological uncertainty in the initial ensemble generation on the final matching results. Two scenarios which have the same semivariogram as the reference field are implemented, and their results show that the initial geological information is important to the history matching performance.     

Wettability and Its Effects on Oil Recovery in Fractured and Conventional Reservoirs

Abstract

The lattice Boltzmann method is a relatively new simulation technique of computational fluid dynamic class. Its several advantages such as dealing with complex boundary and incorporating of microscopic interaction make it an alternative and promising numerical scheme for simulating fluid flow in porous media. Three lattice Boltzmann equation models are introduced and used for calculating permeability of a 2D porous media. Analytical solutions of Poiseuille flow between infinite parallel plates is used for validating lattice Boltzmann equation models. In the numerical simulations the effects of grid resolution and viscosity on the predicted permeability are checked.     

Experiments on Blocking Ability of Nitrogen Foam and Its Application in Anti-Water-Coning

Abstract

Foams have been used successfully in oilfields as a diverting agent to decrease mobility of the gas phase and to control channeling of the water phase in heterogeneous porous media. A series of experiments and numerical simulations focused on foam blocking ability and anti-water-coning technology. The experiments were carried out to measure foaming ability in order to optimize foaming agents. This article discusses the results from several experiments in which factors such as foaming agent concentration, permeability, oil saturation, and gas–liquid ratio were varied systematically to evaluate foam blocking ability. The mechanics of nitrogen foam anti-water-coning are analyzed according to the results of experiments. In order to quantitatively evaluate the production performance by nitrogen foam anti-water-coning, a numerical simulation method was employed to determine the optimal nitrogen injection time, shutting-in time, daily fluid production, nitrogen foam injection method, and nitrogen foam injection occasion. The results of numerical simulations show that nitrogen foam can effectively repress water-coning and allow incremental oil production in a bottom water reservoir.