Data Regularization Processing Technique and Application for Medium-Shallow Tight Gas Reservoirs

In the Jurassic Shaximiao tight gas reservoir in the north Sichuan central slope area, due to its shallow burial depth and short exploration-development cycle, it has become a key domain for quality improvement and efficiency enhancement, as well as one of the new frontiers for natural gas reserve increase and production growth. However, the seismic acquisition in the study area is primarily aimed at shallow-medium-deep three-dimensional exploration. With widespread surface obstacles, the distribution of shot and receiver points is uneven, leading to missing near-offset traces in the shallow layer, low fold density, and poor signal-to-noise ratio (SNR) of data. These issues make it difficult to meet the exploration and development requirements for fine velocity analysis, high-precision imaging, and sand identification in shallow tight gas reservoirs. This paper conducts a field observation system analysis, optimizes the oblique observation system, and carries out five-dimensional data regularization processing for middle-shallow tight gas reservoirs. Applications of actual data show that the SNR and event continuity of the shallow Jurassic Shaximiao Formation tight gas reservoir have been significantly improved, which facilitates the fine identification and high-precision prediction of Shaximiao channel sand.