Abstract

Development drilling decisions in low permeability gas reservoirs can be a challenge. Uncertainty in areal reservoir properties, well completion efficiency, drilling and completion costs, and gas prices make it difficult to quantify deterministic development drilling decisions. Monte Carlo simulation methods provide a means to incorporate reservoir parameter uncertainty into production forecasts in order to understand the range of likely outcomes.

A sample of wells in the Jonah Field, Sublette County, Wyoming is used to develop distributions for reservoir and completion properties. These distributions form the input to a coupled Monte Carlo — Reservoir Performance — Economics Model. Monte Carlo simulation provides the input to the reservoir Performance model. The reservoir performance model predicts flow rate versus time, taking into account completion efficiency (e.g. effective hydraulic fracture length) and the reservoir properties (e.g. permeability, net pay, drainage area, etc.). Finally, for each trial of the Monte Carlo simulation, the production forecast data are input into an economic analysis model. The result is a distribution of economic decision criteria such as net present value and internal rate of return.

The probabilistic distributions for economic parameters, such as net present value or internal rate of return, provide management with a range of likely economic outcomes as a basis for making exploitation decisions. Each economic parameter is quantified not only in terms of the average outcome for the parameter but also in terms of the project risk expressed as the standard deviation of the distribution. The coupled Monte Carlo — Reservoir Performance — Economics Model gives management decision criteria which combines uncertain reservoir performance and economic parameters. The final outcomes are decision criteria that include project average values, reserves, and a measure of risk.