Integration of Sub-Surface Uncertainty with Project Economics Using Probabilistic Risk Modelling and Global Benchmarking of Oil and Gas Projects

Abstract

Abstract The paper presents a novel technique for probabilistic risk modelling to evaluate the feasibility of an exploration and development offshore project. Decisions regarding the feasibility of an offshore project using deterministic methods do not capture the complete range of risks and prospects are ranked based on the net present value with discount factors determined by the company's cost of capital. To improve the decision making strategy, especially in a new exploration asset, a new approach has been worked out in this paper. The results are supported and modelled using a global database of economic parameters related to Capital Expenditure (CAPEX), Drilling Expenditure (DRILLEX), Operating Expenditure (OPEX), development strategy, recoverable volumes which significantly improves the analyst's confidence when ranking new/wildcat exploration prospects. The model integrates multiple offshore development scenarios and accounts for sub-surface uncertainties based on the resource estimates, fluid properties, well productivity. Further, volatility of oil prices, uncertainty range of CAPEX and OPEX estimations are considered to model the market fluctuations and project management risks. The technique is implemented using an analysis performed in three segments. The first part incorporates the creation of a global benchmarking model of more than around 1000 assets that provides the correlation parameters between the variables used in the probability analysis. The second part describes the estimation of a probability distribution model for each variable using an optimizer. This is used as an input to a monte-Carlo simulation model that is calibrated using the global benchmarks and uses the Latin Hypercube sampling method. Finally, the third part provides an offshore field case study to describe the risk modelling and decision-making parameters that are provided as the output. The results of the probabilistic economic analyses include risk profiling based on key performance indicators such as Net Present Value (NPV), and the internal rate of return (IRR). Further, we also present the process to interpret the results with sensitivities related to breakeven oil price, maximum feasible increments in CAPEX, OPEX and the minimum recoverable resource. The results are compared to a global analogue to access the validity and development potential of a project. The paper provides an additional tool for critical management decisions related to exploration and development strategy of a company. The current technology and literature focus on probabilistic modelling of techno-economic variables based on a mean resource volume. However, the current technique fully integrates uncertainties associated with the sub-surface and the other techno-economic variables. This probabilistic technique has all the major advantages of a deterministic approach like it can be quickly implemented, does not have a black box approach and the results are reproducible. It is simple yet robust enough to be quickly deployed on multiple projects in a company.