Sand Production Index Calculation Program Based on Python

ABSTRACT: As the operational cycles of underground gas storage (UGS) increase, sand production in injection-production wells of depleted oil and gas reservoirs has become a significant concern. To investigate the impact of injection-production cycles on sand production severity and location, a sand production prediction curve for these wells was developed. The sand production prediction curve was developed in three steps: (1) deriving dynamic rock parameters from logging data using empirical correlations with mechanical properties, (2) obtaining static rock parameters through empirical formulas, and (3) determining the sand production index to assess sand production. The sand production prediction program for UGS injection-production wells was developed using Python's numpy and pandas libraries for data processing and matplotlib for visualization. The program outputs a sand production index calculation table, logging data curves, rock parameter curves, and sand production index curves. Finally, the accuracy of the program was validated through sand production experiments under alternating loads using a UGS sand production experimental setup. Experimental results demonstrate that the sand production index calculation program, incorporating customizable injection-production cycles, dynamic and static rock parameters, and sand production index formulas, effectively addresses the heterogeneity of formation rocks across different blocks. Additionally, the continuous wellbore sand production results provide valuable references for selecting and implementing sand control completion methods.