The well development plan including the placement of producing and injecting wells during operation significantly influences project economics and resource management strategies. Significant geological and process uncertainty is unavoidable and combines into a vast solution space for equally possible well plans. It is impossible to simulate flow for every possible point within this space and choose the well plan that optimizes production performance. The optimum well plan must be chosen from a smaller and equally fair space of uncertainty Five alternative approaches are available to reduce the number of possibilities and subsequent flow simulation demand:
balance optimum well plans with expert engineering judgment,
collapse the space of uncertainty,
replace the flow simulator with a quick-to-calculate static or dynamic measure,
iteratively optimize a few parameters at a time, or
utilize an experimental design.
The essential elements and implementation details of each approach is described. Examples are collected from different sources in order to illustrate the different approaches.
The primary goal of any reservoir exploitation venture is to generate an optimum well plan scheme to produce as much hydrocarbon as possible. There are several important considerations for this optimization problem including the capital available for drilling and completion of wells, the intended recovery mechanism, the spatial distribution of geological properties, CPU resources, and so on. These considerations can be grouped into two main aspects, the geological description of the reservoir, and the field production system.
Geological heterogeneity is impossible to exactly predict between wells. The unique true distribution of facies, porosity, permeability, and fluid saturations is and will remain unknown. Geological uncertainty is an inherent characteristic of any geological model. Numerical modeling techniques such as geostatistics can be used to quantify uncertainty in the geological model through the construction of multiple equally probable realizations of reservoir properties. Each realization honors the original well data, a structure model, and a userdefined model of spatial correlation. The fluctuation between geological realizations is a measure of geological uncertainty.
The main objective of using geostatistics is to provide realistic models of variability and a fair assessment of uncertainty in production performance due to geological uncertainty. Even the best possible geostatistical practices [1] cannot completely remove uncertainty - the goal is to reduce uncertainty while still being fair. One is always faced with making key decisions such as well plans based on uncertain geology and production.
A small example emphasizes the importance of geological uncertainty for deciding an optimum well plan. Consider in Figure 1 the optimum placement of two production wells for a conventional oil reservoir. Geostatistics is used to generate 10 realizations of a 2D variable that represents reservoir quality over the stratigraphic interval. Darker shades are higher quality. For each realization, the optimum location of the two wells (white bullets) is established based on the centroid of the largest two geo-bodies [2]. A static fractional recovery measure is calculated to replace the flow simulator. The inset table summarizes the recovery of each well plan (WP) and realization (RLZ) combination.
