Abstract

A model is presented for optimizing the number and locations of wells for various hydrologic and reservoir conditions. It can handle confined or unconfined aquifers, leaky or non-leaky aquifers, isotropic or anisotropic permeabilities, existing wells at fixed or model-determined optimal flow rates, complex boundaries, and specified regions to be excluded from possible well location sites for environmental or other reasons.

Examples demonstrate that optimum wellfield design differs significantly from the patterns widely used in the gas industry. optimum patterns depend heavily on the reservoir and hydrologic characteristics of the target, the shape of the project site, existing wells, the total number of project site, existing wells, the total number of wells, and water pressure drop in the coal seam required to commence gas flow.

Introduction

Interest has grown recently in utilizing the vast resources of methane gas associated with deep coal seams. The majority of such methane is held in an adsorbed state on the surface of the coal pores by reservoir pressure; this pressure must be pores by reservoir pressure; this pressure must be reduced to allow desorption of methane from coal surfaces and subsequent methane production. The reservoir pressure is caused by an existing static pressure due to groundwater. Hence, unlike a pressure due to groundwater. Hence, unlike a conventional gas reservoir, gas production is obtained from coal seams by first depressurizing the coal seam, which can itself be classified as a low- permeability aquifer. To do so involves not only permeability aquifer. To do so involves not only reservoir engineering, but also hydrology. Both solve the same pressure or head diffusivity equation. However, the range of applications in each discipline is different. Reservoir engineers, for example, have concentrated more on single-well tests. The concept of skin is used routinely here but is virtually unknown in hydrology. Hydrologists have concentrated more on the use of observation wells, or interference tests. As a result, the range of available solutions is greater in the hydrologic literature for this purpose. The reason for the bias of each discipline is due primarily to the range in permeability and compressibility encountered. Permeabilities in oil and gas reservoir engineering tend to be lower, and compressibilities and well depths greater, forcing engineers to concentrate on the immediate vicinity of the wellbore; for economic reasons interference tests tend to take too long to be practical.

Hydrologists, on the other hand, find the range in conditions more suitable for observation well or interference testing. The production of gas from coal beds often places the engineer in the range of parameters between those which reservoir engineers and hydrologists are accustomed to. Effective exploitation of coalbed methane will involve a synthesis of both disciplines, and consequently the model we develop here will utilize solution techniques from both disciplines.

The parameters to be determined by the computer program are the number of wells, their locations, and individual pumping rates. In the past, hydrologists or engineers have usually attempted to optimize the number and locations of wells for depressurizing with a best guess based on experience, or sometimes using site-specific finite difference models.

This paper presents our progress to date on a computer program for automatically deter-mining the optimum number of wells and their best locations for dewatering/depressurizing for a wide variety of hydrologic conditions. This model can currently handle lease boundaries of complex shape, confined or unconfined aquifers, leaky or non-leaky aquifers, isotropic or anisotropic permeabilities. In the future the model will include vertical fractures and multi-phase flow. This versatility is achieved by using approximate analytical solutions and the method of superposition. The model includes routines to exclude specific regions as possible well location sites. The model can also possible well location sites. The model can also handle the effects of existing wells at a given fixed production rate or the optimum flow rate to be calculated by the model.

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