Standard well screening visual analysis method based on discrete selection model

Abstract

The invention discloses a standard well screening visual analysis method based on a discrete selection model. The method comprises the steps that an adaptive blue noise sampling model is used for keeping overall spatial distribution of standard wells; a multi-scale stratum matching model based on a dynamic programming algorithm is designed, and the similarity degree of well logging is measured from the perspectives of different attributes; prior knowledge of expert users is integrated, a standard well screening method is designed based on a discrete selection model, and effectiveness betweenattribute similarity and a standard well is maximized; an iterative interactive standard well screening method is designed, a user is supported to change the standard well according to priori knowledge, a discrete selection model is updated iteratively, and the standard well screening process and result are optimized. On the basis of comprehensively considering logging space distribution and multi-dimensional attribute information, visual analysis driven supervised standard well screening is achieved, the obtained standard well can represent surrounding logging to the maximum extent, and improvement of subsequent stratum intelligent matching precision and efficiency is facilitated.

Description

technical field [0001] The invention relates to a visual analysis method for standard well screening based on a discrete selection model, and belongs to the technical fields of petroleum exploration, graphics and visualization. Background technique [0002] Three-dimensional seismic wave data and one-dimensional well logging data are two common data types in the field of geological structure interpretation, and a large number of research works have been carried out on geological structure interpretation around the above two data types. Seismic wave data is obtained after recording underground waveform signals with the help of proprietary equipment and performing a series of preprocessing on them, and helps users realize geological structure interpretation through time slice, volume extraction, and other analysis methods. For example, scholars such as Patel designed a seismic wave data analysis method based on two-dimensional slices (Patel D, Giertsen C, Thurmond J, et al. Th...

AI Technical Summary

Problems solved by technology

However, the screening of standard wells relies on the prior knowledge of experts, especially the traditional standard well selection process relies heavily on manual marking. The screening process is not only complicated and time-consuming, but also often fails to consider the spatial distribution of well logs and the correlation of multiple attributes. This brings great uncertainty to subsequent geological structure interpretation, making it difficult to improve the efficiency and accuracy of standard well selection

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