A robust stochastic approach for optimal sequencing of appraisal wells -

Abstract

The life of a hydrocarbon field can be distinguished by five main stages: exploration, appraisal, development, production and abandonment. During the exploration phase, the prospect is located and identified as a commercially viable hydrocarbon reservoir. Following exploration is the appraisal stage, where appraisal wells are drilled to determine the initial hydrocarbon reserves. The development stage consists of determining the recovery technique and the number of production wells whereas in the production stage, monitoring the production and assisting the recovery usually takes place. When the production rates become non-commercial, the field is abandoned and the site is rehabilitated. Of particular interest is the appraisal stage, where the use of seismic data in combination with appraisal wells permits the estimation of the initial hydrocarbons in place and quantification of the associated uncertainties. Since the appraisal stage offers the opportunity to maximize uncertainty reduction, optimizing on this stage makes it the biggest setting for maximizing project profitability. Nonetheless, amid high prices of well drillings and billions of dollars being spent on appraisal activities, limited resources are spent on assessing the usefulness of the gathered information. This thesis proposes a comprehensive approach to determine the number of appraisal wells, their sequence of drilling and their justification based on economic merit. This approach is accomplished through the use of a combination of two methods: the uncertainty reduction method -which ranks locations based on the maximum uncertainty reduction that they can provide- and the Value of Information -which is the difference between the value of developing the project with-without appraisal. The sequential appraisal well location framework will be developed and tested on the Stratton gas field dataset.