The assessment of exploration processes in the Upstream Industry to increase exploration efficiency and promote accelerated drilling decisions.

Abstract

During petroleum exploration, petroleum companies (operators) require efficient hydrocarbon detection and delineation methods to locate petroleum prospects and promote drilling (Selley, 1998). The two pre-drill surveys under investigation in this study are seismic surveys and controlled source electro-magnetic (CSEM) surveys which are used to study the subsurface during offshore petroleum exploration. Drilling dry holes is inevitable, however, a proper and thorough prospect evaluation can significantly increase the chance of success of a prospect (Milkov & Samis, 2020). The purpose of the research is to evaluate seismic and CSEM surveys as secondary hydrocarbon detection tools used to recommend drilling, and to also determine if any of these methods can encourage accelerated drilling decisions and significantly reduce exploration risk. A total of 49 seismic-based samples and 41 CSEM-based samples were used in the study. Survey anomalies were assessed against drilling results to determine the predictive strength of each survey. The Chi-test confirmed that there is a significant association between survey anomalies and attributes such as well results, predictive strength, fluid type and trap style. The researcher analysed the two datasets to determine the probability of an anomaly in each survey and the chance of success if each well is drill based on these surveys. The presence of an anomaly was defined as a positive anomaly (PA) and the absence of an anomaly was defined as a negative anomaly (NA). Fluid type and trap style were used to analyse the predictive ability of the survey anomalies. Seismic and CSEM surveys have indicated a high probability of discovering charged reservoirs in a structural trap as compared to stratigraphic traps, however, CSEM is slightly better than seismic surveys in defining these reservoirs. Both surveys have a low probability of predicting a charged stratigraphic reservoir, although seismic surveys have indicated higher chance of success as compared to CSEM. Positive anomalies observed in both surveys proved to be good indicators of gas-bearing reservoirs as compared to other hydrocarbon fluid. CSEM has a slightly higher chance of predicting oil than seismic surveys. A simplified process mapping for the current offshore exploration processes was conducted. A decision tree was used to analyse seismic and CSEM surveys as secondary tools with emphasis given to their hydrocarbon detection capabilities. Bayesian Theorem was used to calculate the posterior probabilities given that a well is drilled on a positive iii anomaly. The same was applied for wells drilled on negative anomalies. The results have indicated that CSEM has a higher probability of detecting hydrocarbon accumulations as compared to seismic surveys.