ABSTRACT

Risk and uncertainty play an important role in design and operation of complex oil and gas production systems. They are also a driver for business decisions and can have significant implications on capital and operational expenditures (CAPEX and OPEX). A thorough understanding can lead to flexible strategies with mitigations that can limit downsides and capture unexpected upsides. While there has been significant focus on risk and uncertainty in the subsurface (1,2), application of such approaches for flow assurance design and operation has lagged. The work here details concepts and methodologies for evaluating uncertainty from fluid property measurement, to model application, in order to drive risk based decisions. A case study for production application is presented demonstrating the importance throughout the life cycle of an asset.

INTRODUCTION

The evolution of uncertainty assessment and its impact on decision making is rooted in several disciplines dating back several centuries. For example, scenario based planning is used by the military for civil defense, the scientific community for articulating complexity, policy makers for assistance in policy implementation, professional or academic futurists and businesses for long range planning (3). In the oil and gas industry, articulation of uncertainty and long range business planning are critical to success and therefore such approaches have been adapted. One of the earliest adaptors of such approaches was Royal Dutch Shell in the late 60's (3) and as the discipline continued to develop it has been adapted by many others within many industries, including oil and gas. Goode (4) had estimated that US$30 billion in expenditures is lost by the oil and gas industry each year due to poor decisions. While statistical analysis, computing power and advanced algorithms have improved, Bickel and Bratvold (5) stated that based on their data collected from ~500 oil and gas professionals, that more information/data has not made the industry better at making decisions.

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