Application of Multi-Information Fusion Fracture Modelling Based on Neural Network in Carbonate Dual: Medium Reservoir

Abstract

Abstract G oilfield in China is a dual medium oilfield dominated by carbonate reservoir, where faults and fractures are well developed. After G oilfield was put into production, water cut has rised quickly and oil production decreased rapidly. The heterogeneity of fracture development is very strong. Because of unclear understanding of the fracture distribution, oilfield development plan can not accurately identify risks and potentials accurately. As a result, production goals are not as expected. Due to limited core data and imaging logging data, conventional methods cannot characterize fracture information in this oilfield accurately and comprehensively. In order to solve the problems mentioned above, this paper makes full use of logging, geology, seismic and other data to carry out fine characterization of fracture with multi-information fusion fracture modeling based on neural network. Firstly, neural network technology is used to predict the fracture density curves of wells with conventional logging data. Secondly, combined the nonlinear fusion of multiple pre-stack seismic attributes including Tectonic Stress Field, P-Wave AVO and Seismic Discontinuity Detection based on neural network, the fracture density probability model is created to predict three-dimensional distribution of fractures. Thirdly, the fracture Intensity model is set up under the constraint of strict variation function analysis and fracture density probability model. Finally, fracture parameters are obtained according to core observation and imaging logging data, and the fracture network is established by geostatistics modeling method and coarsened equivalent into fracture property model. Blind well validation and dynamic validation are used to verify the validity of fracture model. Under the guidance of research results in this paper, the oilfield development plan is optimized and adjusted. It has also been proved that fracture characteristic of new wells is consistent with pre-drilling prediction result. Most areas with relatively high fracture development degree are corresponding to well groups with faster water cut rising rate. Against the backdrop of global oil economic downturn, fracture modeling technology studied in this paper provides strong technical guidance for oilfield development plan, therefore reducing oilfield development risks and maximizing economic benefits.