A system and method for identifying seismic attributes of fractures

Abstract

The application provides a crack seismic attribute judging system and a crack seismic attribute judging method. The method comprises the following steps: identifying and calculating out crack information of single-well crack density according to acquired imaging logging data and core analysis data, and generating a single-well crack model; extracting seismic attribute data of a specified type from acquired seismic data, and selecting an optimal seismic attribute of which the correlation with the reservoir meets a preset requirement; building a training model by taking the single-well crack model as an input signal and the optimal seismic attribute as an output signal; using an artificial intelligence nonlinear neural network to train the training model; and when the optimal seismic attribute in the training model meets a set screening condition, outputting the optimal seismic attribute meeting the set screening condition. According to the embodiments of the application, the advantages and disadvantages of numerous seismic attributes can be identified intelligently, quickly and accurately, well detection cracks can be identified effectively based on seismic attributes, and the effect and efficiency of actual operation are improved greatly.

Description

technical field [0001] The invention belongs to the field of oil and gas geological exploration and development, and specifically relates to an intelligent identification system and method for determining the coincidence degree between the actual fracture development degree and the predicted fracture development degree of a reservoir based on seismic attribute pre-evaluation. The system can effectively improve work efficiency and has industrial practical value. Background technique [0002] Seismic attributes in oil and gas exploration and development usually refer to special quantities derived from seismic data about geometric, kinematic, dynamic and statistical characteristics. Seismic attributes can be used to analyze and study stored fracture information, thereby providing a reliable basis for storage prediction and well location deployment for oil and gas exploration and development. At present, using seismic attribute analysis technology for oil and gas exploration an...

AI Technical Summary

Problems solved by technology

In the existing technology, manual selection of seismic attribute parameters for fracture identification is often based on experience and subjective analysis, which lacks effective and feasible selection basis, and the correlation between the selected seismic attributes and logging characteristic data is often poor. Big error caused by identification analysis

[0004] At present, there is no specific and feasible implementation scheme in the existing technology that can intelligently, quickly and accurately judge the quality of seismic attributes, so as to provide a reliable basis for storage prediction and well location deployment for oil and gas exploration and development

Images