Development of decision algorithms for resource allocation in exploration and production facilities

In the last ten years the use of Risk-Based Decision Making models (RBDM) has become popular in the oil Exploration and Production (E&P) and Chemical Industry (CI). Government and non-government regulatory agencies; such as the Environmental Protection Agency (EPA), the Office for pipeline safety (OPS), the American Petroleum Institute (API), and the American Society for Testing and Materials (ASTM) have been the driving force behind the development of these models and the inclusion of risk management practices into daily process plant operations.; There are several RBDM models available in the literature that cover risk-based inspection (RBI), risk-based maintenance (RBM) to risk assessment of remediation programs of oil contaminated soil and present the framework of what a RBDM model should be. However, the models available can not be applied to small onshore E&P operations. Onshore E&P operations use different equipment than the equipment for which the existing models were developed for. In addition many onshore operations are relatively small and do not have the financial and technical resources to develop inspection and maintenance plans. Therefore there is a need to develop RBDM models for this sector of the E&P industry.; Risk is defined as the product of the likelihood of failure of equipment multiplied by the consequence (financial and environmental) of the failure. When risk is quantified, management decisions can be made regarding the allocation of resources to reduce the risk. A model that estimates the probability of failure for equipment in small onshore E&P sites for a variety of failure modes is developed. Bayesian analysis was used. The model was calibrated using equipment failure information available through the OPS and the Oklahoma Corporate Commission (OCC). The results of the likelihood model were coupled with an oil spill consequence model developed in a companion project [Wong, 2005] to calculate the risk for E&P equipment.; The calculated risk was used as an input to a decision making model. The decision making model is based on a cost/benefit factor that calculates the cost of risk reduction and helps to identify opportunities to reduce the risk. Costs of equipment replacement/repair were used to calculate the cost benefit factor. The RBDM model can be used for comparison of equipment inside a lease or comparison of different leases to make management decisions regarding the allocation of financial resources.; The Tallgrass Prairie Preserve, in Oklahoma, was used as a case study. Te models developed as part of this research were used to analyze the equipment installed in the field.; The RBDM model presented here can provide necessary equipment reliability information for proactive risk management by providing quantitative information to base allocation of maintenance resources to high risk equipment that will minimize both lost production and ecosystem damage.