Reservoir parameter logging interpretation method based on regression committee machine

Abstract

The invention discloses a reservoir parameter logging interpretation method based on a regression committee machine. The method includes the following steps of 1, selecting logging data sensitive to to-be-predicted parameters as input; 2, normalizing each input attribute value; 3, obtaining reservoir parameters according to results of rock physical experiments; 4, combining the logging data of each layer with experimental data of the reservoir parameters to form a data set; 5, randomly dividing the data set into a training data set body and a test data set body; 6, selecting several intelligent regression algorithms to serve as front-mounted regression predictors; 7, using the training data set body as input and training each intelligent regression algorithm to obtain a corresponding regression prediction model; 8, using the test data set body as input and setting a prediction value by each prediction model; 9, for each set of input data, combining the prediction values set by the regression prediction models, and adopting a committee decision mechanism for setting final prediction values.

Description

technical field [0001] The invention belongs to the technical field of reservoir logging evaluation in petroleum exploration, and particularly relates to a logging interpretation method for reservoir parameters based on a regression committee machine. Background technique [0002] Geophysical logging is a continuous and in-situ geophysical parameter measurement technology along the wellbore. The measurement data mainly include natural gamma, natural potential, deep and shallow resistivity, compensated acoustic wave, density, neutron, etc. These logging data can be used to achieve Reservoir delineation and evaluation of porosity, permeability and saturation. In the conventional reservoir logging evaluation, the evaluation of the above parameters usually adopts the reservoir parameter logging interpretation method model, method and theory, or the empirical formula related to the region. However, for complex formations such as low-porosity and low-permeability reservoirs and l...

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Problems solved by technology

[0010] In order to solve the problem of overfitting and falling into local minimum in a single intelligent regression algorithm, which leads to poor generalization ability, the present invention provides a logging interpretation method for reservoir parameters based on a regression committee machine. On the basis of the intelligent regression algorithm, the decision-making mechanism of the committee is adopted, and the regression prediction of the reservoir parameters is realized by using the logging data

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