A sustainable and preventative warning strategy for the safe production of underground hydrocarbon storage. (10th April 2020) - Zhang, Shengyue; Yan, Yifei; Yan, Xiangzhen
Abstract: This paper considers safe and clean production operating conditions and is a long-term perspective analysis of underground hydrocarbon storage (UHS) injection-production pressure management. For UHS, efficient preventative warning and safe production practices aim to prevent underground hydrocarbon leakage, ensure cleaner production and promote sustainability. A preventative risk warning strategy is proposed based on adaptive supervisory control and a data acquisition system to enhance the uncertainty risk management and control of current underground hydrocarbon safe production sustainability; the copula approach and a Bayesian inference-based approach with an adaptive neuro-fuzzy inference system (Copula-Bayesian-ANFIS) process hybrid framework is presented, completing the risk early warning and control in three steps. The results show that the pressure-dependent uncertainty risk fluctuation range quantified by the probability interval helps to characterize uncertain parameters related to risk sensitivity under dynamic pressure operation. The three dynamic pressure operating parameters (i.e., casing inner pressure, A annular pressure, and B annular pressure) predicted by this application case with ANFIS exhibit a high coefficient of determination (R 2 ) in a quadratic regression model (0.98398, 0.99139, and 0.98462, respectively). The intensity interval of uncertainty risk mapping is quantitatively described according to the significance level and sensitivity; the perturbation error means obtained by fuzzy reasoning for global pressure load sensitivity are 0.01599 MPa, 0.00355 MPa, and 0.00318 MPa, respectively. In addition, the recommended daily mean injection-production pressure allowable gradient control intervals are −1.8–1.5 MPa,  −1.2–1.1 MPa, and −0.4–0.4 MPa, respectively. The uncertainty risk sensitivity quantitative method of the proposed adaptive fuzzy variable enhances the operability of the quantitative description of risk management and sustainable safe production practices. It also has great potential for other types of large-scale underground energy storage systems related to risk control for quantification, characterization, evaluation and safety management. Highlights: A preventative risk early warning strategy promotes sustainability. An early warning model is developed for the optimal management of uncertainty risk. Based on significance level injection-production pressure risk threshold control. The distribution law of pressure balance with multifactor coupling is identified. The elastic risk interval helps manage the operating range with low percentage error.