In this paper, aiming at the challenges of injection–production optimization, especially the contradiction between injection and production in water flooding development of oil and gas fields in China, an interwell connectivity analysis method (TAGNN) based on the time–space scale coupling of injection–production data is proposed. This method uses the existing injection–production well data, combined with the reservoir system seepage mechanics law, to quantitatively characterize and evaluate the interwell connectivity, which overcomes the limitations of traditional methods. The TAGNN method introduces asymmetric time alignment and advanced feature extraction technology to solve the problem of asymmetric injection–production data in time dimension, and considers the spatio-temporal scale coupling characteristics of injection–production data, which can capture the temporal variation and spatial distribution characteristics of data at the same time. The experimental results showed that this method more accurately reflected the interwell connectivity status and improved the fitting and prediction accuracy, compared with the existing GNN method. This method can promote the effective injection of water from the injection well to the production well and optimize the injection production structure and development plan, thereby improving the recovery rate.
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