Use of Bayesian Discovery Process Modeling in support of exploration decisions in the Lower Congo Basin

Discovery Process Modeling is a statistical method used by the oil industry to predict future exploration potential in a basin or play based on the historical discovery sequence. The historical data is used as a non-random sample (largest discoveries found first etc.) from an underlying parent distribution adequately described by lognormality. The Bayesian approach gives the possibility of utilizing prior geological knowledge in an area to constrain the statistical range of input distributions and outcomes (e.g. maximum trap size can be used to constrain maximum field sizes). Mature or semi-mature areas give the possibility to combine geological knowledge with historic experience to make prediction of the undiscovered potential based upon exploration judgments. This study of the Lower Congo basin is to evaluate the exploration potential in a northern and a southern area. The northern area consists of blocks 15, 31 and ultra deep water west of block 31. The southern area consists of blocks 17, 18, as well as part of blocks 32, 33 and 34. Both these areas are part of an Oligocene and Miocene turbidite system. The turbibitic channel sand complex forms the reservoir rock, with an Upper Cretaceous source rock (Iabe Formation). In the blocks 15 and 31 a total of 20 discoveries have been made with recoverable resources ranging from 94 - 725 MMboe. Block 15 is a mature area regarding exploration. Block 31 has three discoveries and is an emerging area. The ultra deep water has not been drilled so far. 21 discoveries have been made in the area of blocks 17 and 18 with recoverable resources between 54 - 975 MMboe. Recent literature has indicated the presence of three distinctive zones along the margins characterized by an extensional regime to the east, an adjacent transitional and a compressional zone in the westward directions. The geological differences in the two areas give different exploration potential. There is also a trend in the southern area that the discoveries that have been found are somewhat larger than in the northern area (Figure 1). An important part of the analysis is to predict the exploration potential in the deep water (compression zone) in the blocks 31, 32, 33 and 34. The method provides estimates of total undiscovered volumes, undiscovered field sizes and number of undiscovered fields as well as uncertainty ranges on these estimates for both areas. Bayesian Discovery Process Modeling has the potential to be a helpful tool to support exploration decisions in the Lower Congo basin. Figure 1. The Discovery Sequences for the blocks 15 and 31 (pink stippled line) and the blocks 17, 18 and 32 (blue line) in the Lower Congo basin. It shows the sizes of the discoveries and the degree of decreasing field sizes with time (hydrocarbon exploration efficiency). Both discovery sequences represent discoveries in the transitional and compressional zone with discoveries in the extensional zone omitted.