As a result of improved technology and declining conventional gas reserves, shale gas (SG) and other tight-rock reservoirs have emerged as significant sources of oil and natural gas.

Since late-2008 natural gas prices have been depressed in North America as a result of oversupply with unmatched demand. Suppressed commodity pricing has made unconventional gas production uneconomic or marginally economic in many areas, which places a greater emphasis on prospect analysis and careful selection of areas of investigation and drilling locations.

This paper discusses a new tool that was developed specifically for generating probabilistic (P10, P50 and P90)1 type curves for shale plays, based on a series of input production wells, which can be used in the early stages of the stochastic analysis of shale gas prospects. This technique will be discussed in detail and a sample case will be given to demonstrate the methodology for a simulated prospect. This methodology combines the use of a cumulative probability distribution (cumulative distribution function – CDF) for a key distribution parameter (i.e. one year cumulative gas produced) with flowing material balance (FMB) to estimate original gas-in-place (OGIP) and drainage area and the square root of time plot analysis to estimate linear flow potential (kmAcm). The results of these analysis techniques are then combined with estimates of other key PVT and reservoir parameters to generate a type curve for each of the probability levels of interest. These type curves can then be used in the stochastic analysis of SG plays using a methodology such as that presented by Williams-Kovacs and Clarkson (2011) for unconventional prospect screening.

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