Intelligent Intermittent Production Optimization for Low-Permeability Reservoirs: A Hybrid Physics-Constrained Machine Learning Approach with Dual-Curve Intersection Control

The efficient development of low-permeability reservoirs is critically constrained by severe geological heterogeneity, marginal permeability (<10 mD), and the consequent prevalence of low-productivity wells. Conventional intermittent production management, reliant on empirical fixed-cycle schedules, fails to adapt to dynamic reservoir behavior and wellbore conditions, leading to suboptimal energy efficiency and recovery. This study presents a physics-constrained, data-driven framework for adaptive intermittent production optimization, specifically designed to address the coupled geological-engineering complexities of such reservoirs. The methodology integrates three core innovations: (1) a hybrid flowing bottomhole pressure (FBHP) decline model coupling a “Three-Segment” wellbore pressure calculation with inflow performance relationship (IPR) curves, enabling dynamic characterization of pressure depletion; (2) a shut-in pressure buildup prediction framework combining a physically interpretable dual-exponential recovery mechanism—representing near-wellbore elastic expansion and far-field formation recharge—with a Random Forest Regression algorithm to capture the influence of geological and operational heterogeneity; and (3) a “Dual-Curve Intersection Method” that autonomously determines optimal pumping and shut-in durations by intersecting predicted pressure decline and recovery curves under geological constraints. Field implementation on 15 low-production wells in the Jiyuan Oilfield—a representative low-permeability asset—demonstrated robust performance: average pump efficiency improved from 14.3% to 14.49%, and average single-well electricity savings reached 15.61%. This work establishes a closed-loop intelligent control framework that bridges reservoir geology, wellbore hydraulics, and machine learning, offering a scalable solution for enhancing energy efficiency and production sustainability in low-permeability and unconventional resources.