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A Construction Method and Application of Oil and Gas Reservoir Permeability Prediction Model

A technology of oil and gas reservoirs and prediction models, applied in prediction, data processing applications, instruments, etc., can solve the problems of insufficient new training samples and low prediction accuracy, and achieve the goals of improving prediction accuracy, ensuring classification accuracy, and increasing search speed Effect

Active Publication Date: 2022-04-22
HUAZHONG UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a construction method and application of an oil and gas reservoir permeability prediction model, which is used to solve the technical problem of low prediction accuracy caused by insufficient new training samples in the construction of the existing oil and gas reservoir permeability prediction model

Method used

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  • A Construction Method and Application of Oil and Gas Reservoir Permeability Prediction Model
  • A Construction Method and Application of Oil and Gas Reservoir Permeability Prediction Model
  • A Construction Method and Application of Oil and Gas Reservoir Permeability Prediction Model

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Embodiment 1

[0039] A method 100 for constructing an oil and gas reservoir permeability prediction model, such as figure 1 shown, including:

[0040] Step 110, obtaining the logging data sample set of the oil well to be tested as the target sample set, and simultaneously obtaining the logging data sample set of the auxiliary oil well as the auxiliary sample set;

[0041] Step 120, selecting a plurality of logging data samples from the auxiliary sample set to form a classification training sample set, and using the classification training sample set and the target sample set as two classes to train a classifier;

[0042] Step 130: Using the trained classifier, generate the correlation between each logging data sample in the auxiliary sample set and the oil well to be tested as the initial weight of the sample, and determine a plurality of samples whose initial weight is greater than the filtering threshold from the auxiliary sample set Logging data samples constitute an auxiliary training ...

Embodiment 2

[0113] A method for predicting the permeability of an oil and gas reservoir, using the oil and gas reservoir permeability prediction model constructed by the method for constructing an oil and gas reservoir permeability prediction model as described in Embodiment 1, to predict the permeability of the oil and gas reservoir.

[0114] The relevant technical solutions are the same as those in Embodiment 2, and will not be repeated here.

Embodiment 3

[0116] A machine-readable storage medium. The machine-readable storage medium stores machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions cause the processor to implement the above embodiments. A method for constructing a permeability prediction model of an oil and gas reservoir described in one and / or a method for predicting the permeability of an oil and gas reservoir as described in the second embodiment above.

[0117] The relevant technical solutions are the same as those in Embodiment 1 and Embodiment 2, and will not be repeated here.

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Abstract

The invention belongs to the field of prediction of oil well reservoir parameters, and in particular relates to a method for constructing a prediction model of oil and gas reservoir permeability and its application. A plurality of samples constitute a classification training sample set, combined with the target sample set to train a classifier; use the trained classifier to generate the correlation between each sample in the auxiliary sample set and the oil well to be tested as the initial weight of the sample, and determine the initial weight from the auxiliary sample set. Multiple samples whose weights are greater than the filtering threshold constitute an auxiliary training sample set; adjust the initial weights of the multiple samples so that the sum of the weights of each sample is not greater than the sum of the weights of each sample in the target sample set; based on the target sample set, the auxiliary training sample set and each sample Weights to train a permeability prediction model. The invention is applicable to the prediction of reservoir permeability when new well training samples are insufficient, and improves the prediction accuracy of oil and gas reservoir permeability under low-proportion training sample data sets.

Description

technical field [0001] The invention belongs to the field of petroleum engineering reservoir parameter prediction, and more specifically relates to a construction method and application of an oil-gas reservoir permeability prediction model. Background technique [0002] Permeability is a characteristic that describes fluid passing through rocks, and is also a key parameter for evaluating reservoir quality in petroleum engineering. It plays an important role in enhanced oil recovery, oil and gas development, reservoir evaluation management, and oil and gas development. If the reservoir permeability can be accurately estimated, it will be beneficial to reservoir evaluation and production optimization, thereby reducing production costs. However, accurate prediction of reservoir permeability is a challenge due to the heterogeneity and complex stratigraphic structure of oil and gas reservoirs. [0003] Reservoir permeability prediction methods can be classified into three types:...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/02
CPCG06Q10/04G06Q10/067G06Q50/02
Inventor 周凯波胡洋翔刘颉
Owner HUAZHONG UNIV OF SCI & TECH