Candidate-well selection (CWS) aims to recognize wells that have potential for higher production after hydraulic fracturing stimulation in petroleum development process, which is natural nonlinear, strong-coupling, uncertain, multi-input, and single-output mathematical problem. CWS hybrid intelligence model is developed by integrating widely applied fuzzy logic systems (FLS), namely, type-2 Takagi-Sugeno-Kang (T2-TSK) FLS, with grey clustering analysis (GCA) for hydraulic fracturing in H gas field of Sichuan Basin, one of the large natural gas field in Southwest of China. The T2-TSK FLS is constructed based on field data involving 49 fractured wells, while the GCA is used to determine the dominant input variables data, and these dominant variables have great influence on post-fractured production. Then we use 39 fractured wells data to train the T1-TSK and T2-TSK FLS to predict post-fractured production. The accuracy of the trained models is validated by comparing predicted post-fractured production with real post-fractured production for the rest of the 10 fractured wells. The evaluation results for the gas field case demonstrate that the T2-TSK FLS is superior to the traditional T1-TSK FLS for CWS using the same input data. The T2-TSK FLS developed in this paper gives high accuracy predicted post-production in H gas field, which is very helpful in selecting the candidate well exactly for hydraulic fracturing.

In risk assessment problems, multiple experts are often involved. On many occasions, assessment experts cannot give crisp scores even if there are scoring standards because of limitation and uncertainty. It is reasonable that the assessment data are expressed in the form of interval numbers with self-confidence. A fuzzy risk assessment model based on interval numbers with self-confidence is proposed in this paper. First, a multi-expert interval numbers with self-confidence fusion model is constructed. In the model, experts weights are determined based on subjective weights and objective weights, and the objective weights are calculated based on the length of the base of interval number and self-confidence simultaneously. Second, a novel method determining the symbolic proportion in an assessment distribution is proposed. This method integrates the concept of similarity measure between generalized fuzzy numbers and the length of the base of intersection of fuzzy numbers. Some properties of the proposed symbolic proportion measure are proved. Third, a fuzzy risk assessment model is proposed based on the fuzzy inference system. The output of the model is a distribution with the possible risk ranks and corresponding symbolic proportions. Finally, an illustrative example which shows the proposed fuzzy risk assessment model effective is demonstrated.

双相介质波传播理论作为油气勘探开发领域的前沿课题,可建立地下储层性质与地面观测数据之间的定量关系,同时可为储层的流体预测提供理论支撑.在阐述储层基本特征的基础上,本文回顾了单一孔隙、含复杂孔隙结构、部分饱和多相流体、各向异性(裂缝系统)双相介质理论的研究进程.同时系统地回顾了基于双相介质理论的波场响应模拟和流体预测方法的发展进程和应用现状,并在前人研究的基础上给出了对地震波场正演和流体预测方法相关研究未来发展趋势的思考和认识,对双相介质理论的应用前景进行了展望.

In view of the characteristics of marine data and the regional imaging challenges, including the poor image of the upper carbonate layers, serious multiple development, the blur image of lower structures caused by shallow gas contained forms, the amplitude anomaly and the energy loss, and the weak seismic reflection signal, in this paper, the integrate processing workflow is designed based on the core pre-conditioning methods consisting of the pre-stack denoising, predictive deconvolution, CMP gather high-precision Radon transform multiple attenuation, combining Q compensation with Q value calculated from viscoelastic medium seismic wave attenuation model. The reverse time migration is adopted to accurately image the complex area, the processed seismic profile delineates the geometry and structural characteristics of the reservoirs.The image of the fault blocks and breakpoints is clear and accurate. The workflow and the methods deployed is proved efficiency in studied area and can be used to solve the imaging problem of similar areas.

岩石脆性评价方法对于非常规油气资源的勘探开发至关重要,其通过计算岩石脆性指数来量化岩石脆性进而用于表征岩石可压裂性,最终服务于非常规油气资源的工业化生产,尽管脆性指标如此重要,由于其物理内涵的特殊性及复杂性,至今业界对岩石脆性没有统一的定义,因此没有统一的岩石脆性评价方法.研究人员出于各自不同的考虑提出了众多岩石脆性评价方法,例如通过确定岩石中脆性矿物及塑性矿物提出的矿物组分法、利用室内岩石力学实验应力,应变曲线中获得的弹性参数及其他特征参数提出的弹性参数法、全应力-应变曲线特征参数法以及利用硬度或强度测试得到的硬度、强度参数提出的硬度法、强度法等,随着近年来的研究深入,许多基于传统方法、原理或不同于传统方法的新型计算方法也得到了更为长足的发展,研究人员对于岩石脆性的定义有了更加深刻的理解,本文对岩石脆性评价常用的方法进行了分析,对计算方法的原理、优越性及局限性等方面进行讨论,并对岩石脆性评价方法的发展趋势进行了展望.

Massive hydraulic fracturing (MHF) technology is widely used to increase the stimulation reservoir volumes in the development of shale hydrocarbon reservoirs by pumping large amounts of fracturing fluids and proppants at a high injection rate. However, fresh water dissipation and the flowback fluid pollution created by this technology brings serious environmental problems. Moreover, the post-production of MHF is uncertain and some fractured wells keep a low production level all the time. It is therefore necessary to find an economical treatment size to satisfy the actual geology position of shale reservoirs, such as mountainous and water shortage regions. The amount of proppant for MHF are a key parameter of treatment size, which also effect the volume of fracturing fluids and injection rate directly. A proppant quantifying model for MHF in a shale hydrocarbon reservoir was developed. In this model, the complex fracture network was characterized as the enhanced permeability area (EPA), and then a correlation was built between the amount of proppants and the EPA based on the Warren-Root model. When the EPA parameters were optimized by a reservoir simulator according to the post-production and net present value, the optimum volume of proppants for a specific shale well can be obtained easily. The new model has been applied at the first horizontal well in Jianghan shale oil field and three horizontal and eighteen vertical wells in Western Sichuan shale gas field successfully. Compared with the results of the early empirical design method used in Western Sichuan, this approach shows a better post-production.

The selection of a target well and formation is considered as the first step in hydraulic fracturing (HF) and naturally regarded as a critical decision-making throughout process of HF treatment. The candidate-well selection process for HF is taken as a complex, nonlinear and uncertainty system. Modern mathematical methods, such as Artificial Intelligence (AI), offer the opportunities to examine the sample data, clarify the relationships among effect factors, in other ways to maximize the concealed potential. However, the performance of these methods is not specified in the certain application of candidate-well selection in gas field. This paper aims to provide a comparison of three candidate-well selection techniques, including BP-ANN, GA-based FNN, and SVM, as well as make clear the most effective one among them to pick a target well for HF. The application result of X gas field shows that BP-ANN is not as effective as GA-based FNN. Despite the advantage of more simple and intuitive evaluation, SVM has its own limitation in the uncertain system.

Abstract XS gas reservoir in Western Sichuan Basin is a typical tight sands hotspot in China, of which the target stratum, namely the 3nd Member of Penglaizhen Formation is braided channel deposition. The sand body with good communication along the river channel is opposite perpendicular to the channel. Moreover, the reservoir with horizontal drilling shows diverse type of sand bodies and strong heterogeneity in vertical and lateral directions. Multi-stage hydraulic fractured horizontal wells have been proven to be effective to enhance gas recovery in tight sandstone gas reservoir. However, one major obstacle has been the previous inability to place the hydraulic-fracture in the complex fluvial tight reservoir to maximize gas production. This paper provides a 3D fracturing design method (3D FDM) considering the influence of various sand-body and flow units on the hydraulic fracture propagation in fluvial tight reservoirs. Firstly, the reservoir was classified into three grades based on its porosity and permeability. A 3D geostatistical reservoir model which was divided into three types, was developed with the sandstone body distributions in vertical and lateral directions. Subsequently, the flow unit boundary was determined by the sand-body permeability and thickness. Then the detailed fracture parameters were implemented in the 3D models and reservoir simulation was used to select the fracture number, space, length and conductivity to achieve economical flow rates. At last, the fracturing simulator was utilized to confirm whether the treatment parameters were appropriate. Results show that the flow unit boundary is a log function of sand-body permeability and thickness. The influence of reservoir grades on fracture space is obvious, which indicates that the fracture space is large in high-grade reservoirs. Comparing various qualities of reservoirs, the fracture length and conductivity in poor-quality reservoirs is considered to be the most significant. Comparison with the fracturing wells with conventional fracturing design method in Xinma gas reservoir, the post-production of the well with 3D FDM increases by 41%, and it shows that 3D FDM is appropriate for the gas development in Penglaizhen Formation.

In recent years, China has a rapid development of shale reservoirs. QianJiang lacustrine shale oil reservoirs in Jianghan Basin are similar to Bakken shale where Multi-stage hydraulic fractured horizontal wells have been proven to be an effective method for reservoir development. In this study, we propose a novel three-step design method for Multi-stage hydraulic fracturing. Firstly, feasibility study on the formation of fracture network was applied to Q2 well by the analysis of brittleness index, the difference of horizontal stresses and the characteristic of natural fissure. Meanwhile the suitable fracturing fluid system was selected and optimized. Then, the fracture network is treated as a high permeable zone. The number, volume and permeability of high permeable zone represent the stimulated reservoir volume and these parameters were optimized by numerical simulation. At last, optimization of treatment parameters (scale and perforation mode) were conducted by the relationship between fracture network parameters (number, volume and permeability) and treatment parameters. We applied the new design method in the first shale oil horizontal Q2 well in Jianghan Basin. Evaluation of postfracture data indicated that the new design method was proper and easy to use. The paper describes a new and convenient design method of multi-stage hydraulic fracturing in shale reservoirs. The lessons learned from fracturing in shale oil formation were also discussed. Finally, further information about stimulation of shale oil formation in Jianghan Basin was provided.