Abstract
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 . 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.
