Water-drive reservoir yield prediction method and device and storage medium

Abstract

The embodiment of the invention provides a water-drive reservoir yield prediction method and device and a storage medium, belongs to the technical field of oil exploitation, and solves the problem of low prediction accuracy caused by single consideration factor of production well yield prediction in the prior art. The method comprises the following steps: acquiring space information and time information of a target oil reservoir well pattern, and establishing a space-time diagram structure data set of the target oil reservoir well pattern; performing sliding time window division on the space-time diagram structure data set, and establishing a training sample set of the target oil reservoir well pattern; training by utilizing the training sample set to obtain a multi-layer space-time diagram neural network for predicting the yield of the water-drive reservoir; and obtaining a yield prediction result of a production well of the target oil reservoir well pattern by using the multilayer space-time diagram neural network. The embodiment of the invention is suitable for yield prediction of the production well in the water-drive reservoir well pattern.

Description

technical field [0001] The invention relates to the technical field of petroleum exploitation, in particular to a method, device and storage medium for predicting the production of water flooding reservoirs based on a multi-layer spatio-temporal graph neural network. Background technique [0002] Water flooding well pattern development is the most commonly used method in the production of conventional oil reservoirs. Predicting water flooding well pattern production is the basis and basis for decision-making issues such as evaluating oilfield production benefits, formulating oilfield development plans, and designing and adjusting well pattern injection-production implementation schemes. in accordance with. Rapid and accurate production prediction for water drive reservoir well pattern is of great significance to realize the regulation and optimization of injection-production well pattern work system for efficient development of water drive reservoir. [0003] Existing produ...

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Problems solved by technology

[0004] The purpose of the embodiment of the present invention is to provide a water flooding reservoir production prediction method, device and storage medium based on a multi-layer spatiotemporal graph neural network, which solves the problem of single consideration factors for production well production prediction in the prior art, which leads to prediction accuracy Low problem, the embodiment of the present invention simultaneously considers the time relationship between production well production and historical production data, as well as the spatial interaction relationship with other wells in the well pattern, effectively improving the accuracy of production prediction

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