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Inter-well connectivity evaluation method based on machine learning

A technology of interwell connectivity and machine learning, which is applied in neural learning methods, biological neural network models, design optimization/simulation, etc., to achieve the effects of improving computing efficiency, fast computing speed, and high accuracy

Active Publication Date: 2020-04-17
北京中科智上科技有限公司
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Problems solved by technology

[0004] Aiming at the connectivity problem between wells in oil reservoirs that cannot be quickly solved by conventional methods, the present invention innovatively proposes an evaluation method for connectivity between wells based on a machine learning model

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  • Inter-well connectivity evaluation method based on machine learning
  • Inter-well connectivity evaluation method based on machine learning
  • Inter-well connectivity evaluation method based on machine learning

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Embodiment Construction

[0031] Embodiments of the present invention are described below with reference to the drawings, in which like parts are denoted by like reference numerals. In the case of no conflict, the following embodiments and the technical features in the embodiments can be combined with each other.

[0032] Figure 1-2 A flow chart of the method of the invention is shown.

[0033] In S1, the sample data set is obtained through numerical simulation technology, and the sample data set includes static data and dynamic data. The sample data sets are for production wells and injection wells.

[0034] The present invention constructs different sample reservoirs innovatively through step S1, utilizes the features contained in the dynamic production data of production wells and injection wells to judge reservoir geological conditions, and considers the influence of multiple factors.

[0035] Specifically, as figure 2 As shown in , a 20×20 (or other sizes) three-dimensional grid structure is...

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Abstract

The invention provides an inter-well connectivity evaluation method based on machine learning, and the method comprises the steps: 1), obtaining a data set which comprises dynamic data and static dataaccording to a numerical simulation technology; 2) performing feature relevance extraction on dynamic data in the sample data set; 3) normalizing the dynamic data and the static data in the reservoirsample; 4) dividing the sample data set into a training set and a test set, and constructing input and output of a machine learning model; 5) training the weight matrix and the bias matrix of the model by using a machine learning method to obtain a training model; 6) verifying the accuracy and effectiveness of the normalized calculation result of the training model; and 7) defining an inter-wellconnectivity coefficient by utilizing the training model according to the stratum average permeability calculated by the dynamic data, and representing the inter-well connectivity. According to the method disclosed by the invention, reservoir geological information is obtained by only needing the dynamic production data of each well, which is most easily obtained in an oil field, so that the inter-well connectivity is obtained.

Description

technical field [0001] The invention belongs to the field of oil field development, and relates to a method for evaluating the connectivity between wells in an oil field, in particular to a method for evaluating the connectivity between wells based on machine learning. Background technique [0002] In the process of oilfield development, due to the low permeability of reservoir geology in my country, the daily oil production of production wells is relatively small. Each oil production plant uses water injection wells to increase the formation pressure by injecting water into the reservoir, thereby increasing the production capacity of each production well. well production. Therefore, understanding the connectivity between production wells and injection wells can optimize the layout of wells, adjust the priority of operations to improve recovery, and is of great significance to the secondary development of oilfields. [0003] There are two types of methods commonly used to ev...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/23G06N3/04G06N3/08G06F111/10
CPCG06N3/084G06N3/045
Inventor 宋洪庆都书一
Owner 北京中科智上科技有限公司
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