Integrated Carbonate Rock Type Prediction Using Self-Organizing Maps in E11 Field, Central Luconia Province, Malaysia

Reducing uncertainty in 3D carbonate rock type distribution is a critical factor that profoundly impacts field development for hydrocarbon or carbon capture and storage (CCS) projects. Miocene reservoirs the Central Luconia offshore region are economically important global gas reservoirs. The nature of these rocks can be visually distinct core multiscale reservoir heterogeneity might vary scale from 100-m to sub-millimeter scale. This work presents series steps workflow obtain spatial information about organization scheme types, most petrophysical sedimentary controls on property E11 field, buildup, located Province, Malaysia. data were generated supervised neural Kohonen algorithm. types predicted with this propagated using IPSOM probabilized self-organizing maps SOM. tool used classifying multivariate samples according “patterns” responses. includes several steps: A Step 1—Core description, B 2—Thin section C 3—Well log interpretation, D 4—IPSOM facies prediction depth plots showed close correspondence core-based terms stratigraphic tight layers, proportions, juxtaposition. result sufficient merit application logs into future porosity model understand lateral vertical distribution. results build realistic digital twin subsurface, geological modeling.