In this paper we present an example of a Coal Seam Gas field evaluation that funnels multiple realisations of the subsurface forecast for different well spacing into a simple visual tool for economic screening of the development opportunities.

The evaluation approach can be described as follows: consolidate the available data in a regional scale geological model; identify the prospective production seams and areas based on a combination of static properties; automatically populate the potential development areas with model wells of different types, completions and lateral spacing; and run the resulting multiple reservoir models in a dynamic simulator. Finally economic metrics, e.g. average gas produced per well, unit cost, or NPV, are applied to the predicted production, and the development options are compared when the metrics are plotted against the total produced gas or well count.

Application of the workflow to an actual project evaluation demonstrated its robustness for the decision making process. The area of interest is about 100 km2 and contains several coal seams, which are proposed to be developed using surface to inseam, horizontal wells. Several well layouts with different spacing between lateral wells were evaluated using multiple subsurface realisations. Proposed wells in each development option were sorted by their median (P50) of predicted produced gas volume and their economic metrics plotted against the total produced gas. If the best wells are drilled first, the economic value of the project starts eroding after a certain number of wells are drilled. This happens because each new well delivers less gas while the cost of the well doesn't reduce at the same rate. The sweet spot is being exhausted. The cloud of well metrics as a function of the number of wells drilled or total gas produced provides an efficient tool for evaluating the optimal size of the project and its economic feasibility.

Due to relatively low permeability of the coal cleat system and large area of interest, the static model had to be split spatially and by seams with the model grid being refined for dynamic simulation. Automation of this workflow made it possible to evaluate multiple development options with multiple subsurface realisations within a tight project timeframe.

The workflow provides a structured framework for selecting economically feasible development options based on the pre-defined criteria while taking into account the subsurface complexity and uncertainty.

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