Refined Prediction Method for Production Performance of Deep-Water Turbidite Sandstone Oilfield: A Case Study of AKPO in Niger Delta Basin, West Africa.

Deep-water oilfields frequently employ large or superlarge well spacing, leading to significant production dynamics influenced by reservoir factors. Traditional methodologies often disregard these influences, resulting in poor accuracy. Therefore, an enhanced prediction methodology rooted in reservoir characteristics is proposed. This approach introduces the dynamic relative permeability law as a bridge, capturing macroscopic oil/water movement within the reservoir. For the first time, it integrates production dynamics with key controlling reservoir factors, encompassing reservoir architecture, injection-production connectivity, and reservoir heterogeneity. The results indicate that (1) In deep-water turbidite sandstone fields with ultralarge injector-producer well spacings, the distribution of oil-water movement is primarily influenced by reservoir connectivity and heterogeneity. The injection water sweeping ability coefficient can quantitatively describe the water flooding capacity, with a strong negative correlation between the injection water sweeping ability coefficient and interwell nonconnectivity coefficient and reservoir homogeneity coefficient. This suggests that better reservoir connectivity or weaker heterogeneity results in stronger water flooding capacity, leading to a wider range of water flooding under the same injection volume. (2) For regions with strong water flooding capacity (injection water sweeping ability coefficient 0.30-0.80), the water-free production period is the main production stage, with a focus on improving the planar flooding conditions. For regions with poor water flooding capacity (injection water sweeping ability coefficient 0.00-0.10), the middle and late water-cut periods are the main production stages, with a focus on improving interlayer dynamic differences in the later stages. For regions with moderate water flooding capacity (injection water sweeping ability coefficient 0.10-0.30), the initial focus should be on expanding planar flooding, followed by a focus on improving interlayer dynamic differences in the later stages. (3) The dynamic relative permeability law, capable of comprehensively portraying the reservoir's influence on macroscopic oil/water movement, emerges as a rational choice for production performance prediction in such contexts. Our method can improve the accuracy, compared with traditional method without geographical factors, from 45% to 90% during water-cut rising stage and 31% to 81% during production declining stage. The high prediction accuracy (90%) observed in the AKPO oilfields underscores the method's efficacy in directing on-site optimization and adjustments for the development of deep-water turbidite sandstone oilfields.