Method for predicting reservoir productivity by using logging facies combined post-stack seismic attributes

Abstract

The invention discloses a method for predicting reservoir productivity by using logging facies combined post-stack seismic attributes, and particularly relates to the field of geophysical exploration.Logging facies modeling standard wells and non-standard wells are divided according to standardized logging curves of all wells in a work area, logging curve principal components of the logging facies modeling standard wells are extracted and subjected to Kmeans clustering analysis, and the optimal clustering number is determined on the basis of an elbow rule to divide logging facies, the same principal components are extracted from the non-standard well logging curve, logging facies are divided by utilizing Kmeans clustering analysis, a logging facies quality model established, reservoir productivity is represented by utilizing logging facies quality, post-stack seismic attributes are extracted, Pearson correlation analysis is performed on the post-stack seismic attributes and the logging facies quality, sensitive seismic attributes are determined, and based on a support vector machine regression algorithm, and a mapping relationship between the sensitive seismic attributes and the logging facies quality is established, and a logging facies quality plane graph is drawn to perform productivity prediction. Accurate prediction of reservoir productivity is realized by using logging facies and seismic attributes, and guidance of oilfield exploration and development is facilitated.

Description

technical field [0001] The invention relates to the field of geophysical exploration, in particular to a method for predicting reservoir production capacity by using logging correlation combined with post-stack seismic attributes. Background technique [0002] Productivity prelayer, as one of the key and difficult issues in the field of geophysical exploration, is a key link in the process of oil and gas field exploration and development, and is closely related to resource evaluation and development plan formulation. [0003] Oil-rich geological information in well logging data. Well logging facies refers to a group of well logging data sets with similar reservoir properties in the underground. By classifying logging facies, strata can be divided into multiple longitudinal strips with different geological significance . Scholars at home and abroad have done a lot of research on reservoir prediction using well logging data. In 1987, Pierre et al. used Bayesian decision-makin...

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Problems solved by technology

[0006] At present, the single well productivity prediction using the drilled single well logging data has been realized, but the productivity prediction for the drilling area in the work area has not been realized. At the same time, there is no prediction using the combination of logging facies and seismic attributes. Therefore, there is an urgent need to propose a method for predicting reservoir productivity by combining well logs with post-stack seismic attributes

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