Logging phase recognition method based on a fuzzy theory and a neural network

Abstract

The invention provides a logging phase recognition method based on a fuzzy theory and a neural network, which comprises the following steps: firstly, constructing a fuzzy region convolutional neural network, putting a given target assumed region and target recognition into the same network, sharing convolution calculation, and updating the weight of the whole network in a training process; next, performing convolution and pooling operation on the logging data through a fuzzy region convolutional neural network; interacting the convolution layer and the pooling layer; carrying out fuzzy operation on the convolution layer and the pooling layer; starting from a first layer of a fuzzy region convolutional neural network so that the number of fuzzified layers is gradually increased; adjusting the number of fuzzy layers according to different data sets, the last layer of the fuzzy region convolutional neural network obtains a feature vector, the feature vector maps features into a low-dimensional vector through a sliding window, then the features are input into two full-connection layers, one full-connection layer is used for positioning, and the other full-connection layer is used for classifying.

Description

[0001] Divisional Application Statement [0002] This application is a divisional application of a Chinese invention patent application with the title of "A Parallelization Method for Convolutional Neural Networks in Fuzzy Regions in a Big Data Environment" and the application number is 201610762101.1 filed on August 30, 2016. Technical field [0003] The invention relates to the technical field of petroleum logging, in particular to the field of big data logging. Background technique [0004] Logging information and sedimentation are the reflection and control factors of the petrophysical properties of the formation. Therefore, logging data has always been used as a basic and important source of information in the study of oil and gas reservoir sedimentology. Logging facies is the logging information and reservoir deposition. The bridge between academic characteristics. For most oil and gas wells, logging data is the only comprehensive information source covering the entire well s...

AI Technical Summary

Problems solved by technology

In recent years, the oil industry has established a large number of cloud data centers, but the utilization rate is not high, and resources are seriously wasted

One of the important reasons is the lack of big data processing platforms and corresponding big data technologies to make full use of these computing and storage resources.

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