Intelligent Appraisal Program for a Multi-Prospect Development

摘要

While many companies are hunting for elephants, exploration results in deep offshore plays over the past years show the increasing trend away from giant field discoveries towards smaller fields in the 50-100 million bbl range, which tend to be geographically dispersed. These resources need to accumulate to a critical mass to justify an economically viable development. How likely is this to happen? Which objects must be included in the resource base? Which drilling program should be planned to reach an early decision? Given the huge costs involved, answers cannot rely on the subjective choice of a few deterministic scenarios. A novel methodology is proposed to evaluate the potential for a hub in a deepwater multi-prospect development. The approach relies on a probabilistic model of the risks and uncertainties of the resource base, illustrated by a real case study including five discoveries and four prospects, 10-30 km apart. Each object must pass a minimum resource threshold to justify its connection to the hub. Then a global threshold is applied to the complete development. The performance of a proposed appraisal program is quantified by statistical indicators obtained by simulating a large number of drilling outcomes which are stored in a scenario database. Three indicators capturing the three elements of Decision Analysis (states of nature, decisions, payoffs) prove useful. These are respectively: the distribution of the resource potential in the ground; the probability of a development decision based on the cumulative discovered exceeding the threshold; and the distribution of developed resources. The last two elements define the traditional economic decision tree. Intelligence is introduced in the appraisal program by reassessing the situation after each well and evaluating the probability of meeting the threshold with the remaining wells. If it is low (10% or less) appraisal is stopped, or its scope reduced. Early quitting minimizes well count in the dry branch of the economic decision tree, which has a great impact on risked economics. Optimizing the drilling order may also reduce the number of wells needed to reach a decision. Thus an efficient appraisal program with firm and contingent wells can be defined.