Integrity tests, inspections (caliper log) and maintenance activities are critical to the integrity management of the production tubing and are important to ensure that loss of production — due to e.g. excessive reduction in the wells cross-section and numerous unplanned shut-ins, is reduced over the service life while maintaining safety and availability. The progressive loss of integrity of production resulting from deterioration processes such as scaling, are time variant with large uncertainties. The time variability together with large uncertainties is one main driver of increasing need of rational tools for cost-optimal planning of inspections and maintenance. Optimal planning of inspections and maintenance is therefore necessary to achieve timely and risk-efficient management of the production wells by finding a trade-off between the cost of inspection and maintenance, and the benefit of increased production amongst others.
This paper presents a framework for identifying cost-optimal planning of inspections and maintenance of the production tubing of sub-surface oil and gas wells subject to time dependent scale degradation. The proposed framework is based on a risk-based approach, which allows uncertainties to be accounted for. By adopting this approach, the strategies which give the minimum expected value of the total cost of inspection and maintenance are identified. In this paper, the approach uses categorization of the sizes of scale thickness characterized by damage sizes, and inspection results into damage states, and takes into account imperfection in the inspection results in terms of the probability of detection and damage sizing accuracy. For each of the damage states, a certain damage cost and maintenance decision rules, stating the next line of action, are established. The inspection and maintenance decision problems are therefore modeled based on the pre-defined decision rules while the optimization parameters are the intervals of inspections and the maintenance alternatives. The probabilistic model, accounting for uncertainties, scale propagation proposed by Guan et. al. (2019) is used to describe the scale growth or damage evolution. Bayesian pre-posterior decision theory is the basis for the decision making. All costs — including damage, inspections and maintenance costs, through the lifetime of the production tubing are evaluated and included in the decision model and the expected value of the life cycle costs are estimated and compared for different maintenance alternatives. An example in the paper demonstrates the framework and the implementation of the decision rules for one sub-surface production well subject to calcite scales.