Sedimentary microfacies depicting method

Abstract

The invention provides a sedimentary microfacies depicting method which combines well logging information, geological data and planar seismic data of single points of completed well drilling points inthe longitudinal direction to realize well seismic combined fine depicting of deposition microfacies. The microfacies depicting precision is improved through one-way regression analysis, clustering analysis of preferable seismic attribute parameters. A multi-element linear regression method is combined with the seismic attribute parameters so as to obtain a fitting relation function model. The geological parameters of the well points are fully utilized through a thinning step, and the geological parameters converted by the seismic attribute parameters of the virtual well points between the completed well drilling points are effectively utilized, so that the finally-depicted sedimentary microfacies precision is higher. In addition, only partial seismic attribute points are extracted, so that the workload is greatly reduced in actual operation, and the labor cost is reduced. The reservoir distribution among wells can be predicted on the basis of the sedimentary microfacies depicted by the method. A geological basis is provided for well deployment, and the exploration and development success rate of the oil and gas field is improved.

Description

technical field [0001] The invention belongs to the field of petroleum development and relates to a deposition microfacies characterization method. Background technique [0002] The traditional study of planar sedimentary microfacies generally counts the data of formation thickness, sandstone thickness and sand content of each layer on a single well, considers the shape of logging curves of each layer of each well, and uses well points as control points to outline the work area. Contours within the sand body, and then analyze the distribution of sand bodies on the plane and determine the distribution of sedimentary microfacies in the work area. [0003] At present, the study of sedimentary facies using seismic data mainly includes inversion and seismic attribute analysis. The inversion method is currently multi-well constrained inversion, but due to too much consideration of well information, its predictability is limited to a certain extent. The seismic attribute method is...

AI Technical Summary

Problems solved by technology

This has the following problems: when determining the relationship between seismic attribute parameters and geological parameters, there is a certain correlation between the two, but it is not a one-to-one linear relationship, but there is a correlation coefficient

Therefore, if this correlation relationship is used to transform seismic attribute parameters, and the size of the correlation coefficient is ignored, there must be a large error

Moreover, if the work area is large and there are many seismic attribute points, when converting seismic attribute parameters into geological parameters, the transformation workload will be relatively large

Images