The objectives of this work were to achieve realistic reservoir modeling using seismic inversion volumes, advance petrophysical & rock typing analysis for predictive modeling of reservoir quality sands of Lam Formation. Generation of predictive scenarios for the constructed reservoir model for reduction in uncertainty. Identification of new infill well locations based on the predictive reservoir sand distribution. Reevaluation of in place volumetrics for Lam Formation in Prospect D Field. The methodology adopted to achieve the above results.
The methodology for this work contained the following steps; In the first step seismic inversion was performed on Prospect D Field 3D seismic dataset to obtain volume of clay seismic volumes and facies volume. Petrophysical rock typing combined with the core data analysis was sued to calibrate the inverted volumes by identification of clay typing. The seismic inversion volumes were integrated with the depositional settings of Lam Formation to qualitatively interpret the inverted volumes. Reservoir modeling was performed using seismic inversion facies volumes and petrophysical rock type model to predict and distribute the different depositional facies being controlled by inversion trends. Generation of In place volumes and predictive scenarios for reduction in uncertainty and attributing more predictive strength to the reservoir model.
On the basis of reservoir modeling two (2) prospective areas were observed to show good quality sand bodies which were non-tight and reflected good reservoir properties. The seismic inversion volumes captured the depositional trends within the Lam Formation showing the variation between channel complexes to reservoir quality delta sand bodies. Two (2) to Four (4) infill well locations were identified along with forecasted results which showed positive results based on the delineated prospective areas. The seismic inversion volume results, petrophysical rock typing combined with core data completely changed the field development plan by identifying new prospective areas which were not identified or interpreted previously.