--> Mitigating Variability in Uncertainty and Risk?

AAPG Asia Pacific Technical Symposium

Datapages, Inc.Print this page

Mitigating Variability in Uncertainty and Risk?

Abstract

For management to make good decisions, they must have reliable estimates of the risked resources they can expect to encounter. The guidelines established in the Petroleum Resource Management System (PRMS) require companies to define the range of uncertainty for each project, typically defining the P90, P50 or Pmean, and the P10. Three studies indicate that there is considerable variation in the amount of uncertainty and risk between interpreters and between methodologies. The first study examines the uncertainty introduced from different interpreters. Eight students were given a 3D data set over a prospect. All elements of the volumetric equation were provided except for the area of closure, which was determined from their maps. The un-risked mean volumes estimated by the students ranged from 93 to 202 MMBO. The risked mean volumes ranged from 17 to 42 MMBO. These distributions were strongly skewed by one outlier. Removing the outlier gives us much more realistic range of 93 to 109 MMBO (unrisked) and 17.23 MMBO (risked). The challenge, however, is how do we ensure the maps provided to management are representative, or an outlier? To determine if any one map is an outlier, management would need to have a minimum of three maps. Since companies cannot afford to have three interpreters work the same prospect or field, they need a different means to determine if an interpreter’s maps represent the norm, or are an outlier. This can be established by conducting systematic look-back reviews of all wells, both dry holes and discoveries. Over time, lookback reviews will help determine if an interpreter is introducing a systematic bias. The second study examines the range of uncertainty resulting from the methodology used to estimate the volumes. A field study was conducted, with the in-place reserves being estimated using multiple volumetric methodologies; deterministic, Monte Carlo, probabilistic, MBAL, decline curve analysis, and a geomodeling. Each method resulted in a different estimate of the volumes and the range of uncertainty. For several methods, the range between the minimum (P90) and the maximum (P10) varied by well over 100%. The range of the most likely or Pmean volumes for the various methods had a range of approximately 12%. Using multiple volumetric methodologies can hel reduce the range of uncertainty. The third study examined risk. Several individuals were asked to risk a prospect. The chance of success for each individual was very close (22 to 25%). However each individual arrived at that COS by very different means, one assessing the key risk to be trap, another as charge, and the third identified the key risk as reservoir. This indicates that risk is highly subjective, with individuals having a COS in mind, and then getting to the COS by various paths. Although the overall COS determined by the various individuals was reasonable, the principle risk identified by them was different. Management must know the critical risk for any project in order to make sound investment decisions. The Delphi Method can be used to help management determine the critical risks for a prospect. In the Dephi method, a group of individuals review a prospect and then write down their assessment of the source, migration, reservoir, trap, and seal risk. After each individual has written down their assessment of the risk, the team reviews and discusses each individual’s assessment. Following the discussion, each individual writes down their new assessment of the risk. This method eliminates peer and management pressure and helps the team to develop a consensus of the risk.