Interwell测井约束地震地层反演应用研究

Interwell测井约束地震地层反演是用测井和地震资料作为约束条件,充分利用先验的地质信息,以模型作为约束,通过反演得到反映地层本质属性的绝对波阻抗资料,从而对储集层进行精细描述的一种技术。利用interwell软件,结合生产部门的实际资料,通过提取的子波和处理后的测井曲线建立了约束模型,并在模型约束下对中江地区沙溪庙组的主力含气砂岩进行反演,预测判别了砂岩的顶底边界,并通过工作中遇到的问题及其解决方法,对Interwell反演给出一个从感性到理性的认识。

On the uncertainty of interwell connectivity estimations from the capacitance-resistance model

The capacitance-resistance model （CRM） is an alternative to conventional reservoir simulation. CRM, a simplification of complex numerical models, uses production and injection rates to infer a reservoir description. There is no prior geologic model. The principal output of CRM fitting is the fraction of injected fluid （usually water） that is produced at a producer at steady-state. These fractions are interwell connectivities. Interwell connectivities are fundamental information needed to manage waterfloods in oil reservoirs. The data-driven CRM is a fast tool to estimate these parameters in mature fields and allows one to make full use of the dynamic data available. This paper considers the problem of setting an upper bound on the uncertainty of interwell connectivities for linear-constrained models. Using analytical bounds and numerical simulations, we derive a consistent upper limit on the uncertainty of interwell connections that can be used to quantify the information content of a given dataset.

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Analytical Determination of Interwell Connectivity Based on Interwell Influence

Interwell connectivity, an important element in reservoir characterization, especially for water flooding,is used to make decisions for better oil production. The existing methods in literature directly use related data of wells to infer interwell connectivity, but they ignore the influence between different wells. The connection of one well to more than two wells(as is often true in the oil field well pattern) will impact the accuracy of the connectivity analysis. To address this challenge, this paper proposes the Particle Swarm Optimization-based CatBoost for Interwell Connectivity(PSOC4IC) based on relative features to analyze interwell connectivity with the combination of joint mutual information maximization-based denoising sparse autoencoder for inter-feature construction and extraction and PSO-based CatBoost(PSO-CatBoost) for connectivity prediction with high-dimensional noise data.The experimental results show that the PSOC4IC improves analysis accuracy.

An intelligent prediction method of fractures in tight carbonate reservoirs

An intelligent prediction method for fractures in tight carbonate reservoir has been established by upgrading single-well fracture identification and interwell fracture trend prediction with artificial intelligence,modifying construction of interwell fracture density model,and modeling fracture network and making fracture property equivalence.This method deeply mines fracture information in multi-source isomerous data of different scales to reduce uncertainties of fracture prediction.Based on conventional fracture indicating parameter method,a prediction method of single-well fractures has been worked out by using 3 kinds of artificial intelligence methods to improve fracture identification accuracy from 3 aspects,small sample classification,multi-scale nonlinear feature extraction,and decreasing variance of the prediction model.Fracture prediction by artificial intelligence using seismic attributes provides many details of inter-well fractures.It is combined with fault-related fracture information predicted by numerical simulation of reservoir geomechanics to improve inter-well fracture trend prediction.An interwell fracture density model for fracture network modeling is built by coupling single-well fracture identification and interwell fracture trend through co-sequential simulation.By taking the tight carbonate reservoir of Oligocene-Miocene AS Formation of A Oilfield in Zagros Basin of the Middle East as an example,the proposed prediction method was applied and verified.The single-well fracture identification improves over 15%compared with the conventional fracture indication parameter method in accuracy rate,and the inter-well fracture prediction improves over 25%compared with the composite seismic attribute prediction.The established fracture network model is well consistent with the fluid production index.

多井约束地震地层反演技术在川西致密砂岩气藏描述中的应用

四川盆地川西坳陷陆相致密碎屑岩油 /气储层具有致密、低孔渗、薄层交互、多层叠置和强非均质性的特点。长期以来 ,这种油 /气藏的勘探开发一直是世界性难题。近年来 ,积极推广应用新技术、新方法 ,以新思路、新认识指导勘探开发 ,特别是 2 D/3D井间多井约束地震地层反演技术的开发和推广应用 ,配套和完善了川西致密非均质气藏描述技术。多井约束地震地层反演利用高精度三维地震资料 ,结合测井、地质、钻井、测试等资料 ,在研究确定气藏分布范围、空间几何形态描述、储集参数反演。

Quantitative description of characteristics of high-capacity channels in unconsolidated sandstone reservoirs using in situ production data

Quantitative description of the high-capacity channels in unconsolidated sandstone reservoirs, into which water was injected to improve oil recovery, is a hot topic in the field of reservoir development. This paper presents a novel approach to describing quantitatively the characteristics of connected macropores in unconsolidated sandstone reservoirs using in situ production data. Based on physical simulation for formation mechanisms of high capacity channels and interwell tracer test data, a mathematical model was established to describe high-capacity channels by grey correlation theory, flow mechanism of fluid in porous media and reservoir engineering, and a program was developed to describe quantitatively the channel characteristics. The predicted results were consistent with field monitoring data （80%）, so this model could be economically and effectively used to identify high-capacity channels.

A Model for the Connectivity of Horizontal Wells in Water-Flooding Oil Reservoirs

As current calculation models for inter-well connectivity in oilfields can only account for vertical wells,an updated model is elaborated here that can predict the future production performance and evaluate the connectivity of horizontal wells(or horizontal and vertical wells).In this model,the injection-production system of the considered reservoir is simplified and represented with many connected units.Moreover,the horizontal well is modeled with multiple connected wells without considering the pressure loss in the horizontal direction.With this approach,the production performance for both injection and production wells can be obtained by calculating the bottom-hole flowing pressure and oil/water saturation according to the material balance equation and a saturation front-tracking equation.Some effort is also provided to optimize(to fit known historical production performances)the two characteristic problem parameters,namely,the interwell conductivity and connected volume by means of a SPSA gradient-free algorithm.In order to verify the validity of the model,considering a heterogenous reservoir,three conceptual examples are constructed,where the number ratio between injection and production wells are 1/4,4/1 and 4/5,respectively.It is shown that there is a high consistency between simulation results and field data.

A Method for Identifying Channeling Paths in Low-Permeability Fractured Reservoirs

Often oilfield fractured horizontal wells produce water flowing in multiple directions.In this study,a method to identify such channeling paths is developed.The dual-medium model is based on the principle of inter-well connectivity and considers the flow characteristics and related channeling terms.The Lorentz curve is drawn to qualitatively discern the geological type of the low-permeability fractured reservoir and determine the channeling direction and size.The practical application of such an approach to a sample oilfield shows that it can accurately identify the channeling paths of the considered low-permeability fractured reservoir and predict production performances according to the inter-well connectivity model.As a result,early detection of water channeling becomes possible,paving the way to real-time production system optimization in low-permeability fractured reservoirs.