Evaluation of Unconventional Resource Plays

Abstract

Making sound business decisions in one of the hottest domestic exploration plays, unconventional gas, offers a set of challenges not usually encountered with more traditional opportunities. Unlike with standard prospect and conventional play risk analysis, geologic chance is not a major issue, and estimates of initial production, decline rates, mechanical efficiency, and success planning dominate the analysis rather than traditional volumetric determinations. The valuation and assessment of unconventional or "continuous resource" opportunities is not feasible using traditional probabilistic, volumetric-based methods. A fully stochastic business, value-chain model is the best way to assess the potential of an unconventional play. Such an evaluation method allows for multi-disciplinary and cost input that affords decision makers with the appropriate data to make good decisions. The boundaries of unconventional reservoirs extend well beyond the limits of most individual acreage holdings. As such, the recommendations of Schmoker and others to base the full resource availability on a cell or single well drainage area should be embraced as a starting point. Resource uncertainty is handled by a continuum of well size distributions arranged to form an EUR Envelope. Volumes are only part of the equation, however. Uncertainty in the production profile must be taken into account, with variations in initial production, decline rate, and hyperbolic exponent figuring prominently in the final assessment of profitability. There are four main stages in the exploitation of unconventional opportunities: Exploration, Evaluation, Delineation, and Development. Proper assessment, including identification and management of downside risk, requires a decision-focused, integrated, multi-discipline evaluation process through the four stages. Unconventional plays use an initial number of wells to test the viability of a play and stimulation technology/methods. These pilot programs can be optimized, for number of wells, and company risk tolerance. Pilot Effectiveness is the (measurable) probability of the pilot program providing truthful results given the small number of test wells modeled. Output from the proposed stochastic evaluation method include both single economic and product-based metrics in cumulative probability curves, as well as time series output in both aggregate and pathway forms. A thorough understanding of results analysis, Value of Information, and decision options is encouraged in order to take full benefit of the stochastic assessment method. Introduction In recent years, resources recoverable from reservoirs of difficult nature have come to be called "Unconventional Resources". In addition to fractured reservoirs, unconventional plays include tight gas, gas/oil shale, oil sands, and coal-bed methane (CBM).

Coalbed-Methane Pilots—Timing, Design, and Analysis

“…There has not been a comprehensive model for planning the exploration and evaluation of a CBM play. A number of authors have addressed to some degree of detail individual phases of the assessment process for CBM while only briefly touching on the other pre-or post-phases in the assessment process (Puri et al 1995;Blauch et al 2002;Green et al 2003;Haskett and Brown 2005;Weida et al 2005;Rodvelt and Oestreich 2005;Clarkson and McGovern 2005). The aim of this paper is to develop a morecomplete, -consistent, and -accepted approach to the evaluation of CBM opportunities.…”

Decision Analytics, Value of Information, and Piloting in Unconventional Reservoirs

“…These results should be compared to approach developed by Haskett and Brown (Haskett and Brown, 2005). While Haskett and Brown do not present these charts we can calculate them from their Figure 16.…”

Maximising the Value of Unconventional Reservoirs by Choosing the Optimal Appraisal Strategy

“…These include Gray et al (2007), Stabell et al (2007), Gouveia et al (2009), Williams-Kovacs and Clarkson (2011), Giles et al (2012), Ingsoy et al (2013), and Allan (2013). Haskett and Brown (2005), Willigers et al (2014), and Bickel (2014) demonstrated how the initial view of the projected well performance in a reservoir can be revised using Bayes' rule as new data come to light by applying the general principles developed by Schlaifer (1959) over fifty years ago.…”

“…The total set of production data gathered from wells that were drilled in different phases of an appraisal programme should be used in the assessment of the reservoir. Hence, the reliability of an appraisal programme is determined not solely by the number of pilot wells (Haskett and Brown, 2005;Bickel, 2014) but also by the length of time the wells have been produced.…”