This paper presents an analysis of the coalbed degasification process. The theoretical and experimental basis of the degasification process are discussed and a simulation model which incorporates all aspects of this process is described. The simulator is demonstrated using actual field data developed by a joint industry/government demonstration project funded by the DOE and U. S. Steel. The basic reservoir description is discussed in detail, including variations of important description parameters with location.Initial and boundary conditions are demonstrated and analyzed. Initially, the coalbed was saturated with water. With water production, reservoir pressure is lowered, causing gas to desorb from the coal creating a mobile gas saturation. Subsequently, interwell interference effects are demonstrated and the need for such effects explained.Finally, the long term gas deliverability of the pattern is forecast. This forecast shows that about 45% of the gas within the pattern can be removed if the pattern is in operation six years ahead of mining.

Improved Methods of F o n i t o r i n g Water Production General Method of Removing and Measuring Gas. .

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Conventional wisdom states that a coalbed methane (CBM) evaluation program should consist, initially, of core hole and permeability testing, followed by flow testing wells, leading to one or more multiple well pilot programs. Such an evaluation program progresses sequentially from lower initial cost for basic data acquisition to higher cost production testing that normally focuses on the construction of a reservoir simulation-based field development model. However, Applications of this approach minimize any consequence of reservoir heterogeneities, which ultimately dominate later large-scale project performance. Due to these heterogeneities, potentially commercial coalbed methane production areas may be bypassed or prematurely condemned. To reduce the likelihood of missing or overlooking otherwise attractive CBM plays, an alternative evaluation model was developed to focus specifically on reservoir heterogeneity. This alternative evaluation program utilizes production distributions derived from proven productive basin area reservoir/operational analogs. The resulting production variability is then weighed against prospective new play areas in order to define more effective exploration program requirements. This results in a more realistic approach to the exploration process and increases the probability of large-scale technical and financial success. Introduction Development of a new CBM leasehold area requires an initial assessment program to define ultimate field producibility. The program is designed to acquire the required type and amount of data to forecast optimizal field performance while minimizing the expenditure necessary to disprove financial viability. Therefore, the evaluation process requires balancing assessment costs with the risk of over-funding development within an uneconomic or marginal asset. An often unrecognized but critical component of making these balanced decisions is the relative confidence level of the data generated from such an evaluation program, given the inherent variability of coal seam reservoirs across the leasehold area. Many coal basins have numerous core holes associated with mining activities and well logs associated with conventional oil and gas exploration and development. These data usually provide the means to develop an initial understanding of the coal seam geometry (depth, thickness, dip, and number of zones) and drives CBM exploration within any given area. These calculated coal resource parameters are then combined with measured gas content, sorption isotherms, coal chemistry, and estimated depth/pressure relationships to estimated gas in place. Thus, by combining existing information with a limited quantity of new core-derived data, a relatively confident geologic model of the gas resource in place can be developed. However, the level of confidence obtained from production forecasting is often much lower. Production from CBM wells is primarily a function of gas resource in place, flow capacity (permeability and reservoir pressure), and completion effectiveness. With resource (gas in place) broadly and confidently defined and given that reasonable completion techniques are utilized, then leasehold production ultimately becomes primarily a function of reservoir flow capacity, predominantly permeability. Unfortunately, by its very nature, coal seam permeability typically varies significantly from area to area, location to location, and even within areas smaller than an acre. This paper describes how this aspect of permeability, in terms of ultimate flow capacity of a leasehold area, is conclusively defined by using the acquisition of a statistically significant sampling of well data test sets.

This paper was selected for presentation by an SPE Prognun Committee following review of information contained in an abstract submitted by tho autbor(s). Contents of tho paper, as presented, have not been reviewed by tho Society of Petroleum. Engineers and are subjected to oorrcction by tho autbor(s). The material, as presented does not neoessarily reflect any position of tho Society of Petroleum. Engineers, its offioers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of tho Society of Petroleum. Engineers. Permission to ropy is restricted to an abstract of not more than 300 words. lliustrations my not be oopied. The abstract sboold oontain OOI18piC\lOU8 acknowledgement of where and by whom tho paper was presented. WriteLibrarian, SPE, P.O. Box 833836, Richardson, TX75083-3836, U.S.A., fax 01-214-952-9435. AbstractThis paper presents the first field scale measurements of insitu stress effects on permeability of coal seams. The importance of these effects on a highly compressible reservoir such as coal is demonstrated by relating permeability and production to stress.Well testing complications and the implications of stress toward exploitation of existing reserves and exploration for new reserves are also discussed. Additionally, comparisons of this paper's findings to prior theoretical work, core testing, and limited field data are presented.