oa Multi-Component Analysis into Reservoir Connectivity in Complex Fluvio-Deltaic Hydrocarbon Fields, Gulf of Thailand

Fields in the Gulf of Thailand are currently focused on optimizing infill well placement to maximize extraction from both shared and unshared hydrocarbon reservoirs. This strategy utilizes an advanced Gulf of Thailand model that integrates specialized concepts of infill well spacing. A key objective is to identify new reservoirs to unlock additional potential from these wells.

Traditionally, reservoir connectivity is identified using wireline logging, pressure tests, and geological data. Relationships between the width and thickness of sandstone bodies in specific depositional environments help predict reservoir connectivity. The methodology involves manual identification of reservoir connectivity and facies based on well data. The distance to connected reservoirs is measured and projected to determine true channel width trends, validating width-to-thickness ratios by facies and units. A Random Forest regression model assesses parameter influences to predict true channel width and sand connectivity among wells.

The width-to-thickness ratios differ significantly between the channel (1:20 to 1:700) and bar (1:200 to 1:450) sandstone facies, reflecting distinct reservoir geometries and connectivity patterns. The model’s accuracy is validated using Leave-One-Out Cross-Validation, achieving high performance (80%-90%) across geological units. This predictive tool supports new reservoir identification and optimization of reservoir productivity in the Gulf of Thailand.