Enhancing Advanced Completion Design Through Permeability Evaluation in Heterogeneous Carbonate Reservoirs Using Integrated Multiple Logging While Drilling Measurements

Abstract Lateral changes in petrophysical parameters and diagenetic effects introduce uncertainty in porosity-permeability transforms in complex carbonate reservoirs. This results in discrepancies between actual downhole production and permeability profiles in horizontal wells. Designing sophisticated completions requires high confidence in predicted permeability to achieve lateral flow equalization and maximum oil recovery. This paper presents a model, to improve lower completion design and permeability prediction, by integrating multiple technologies such as nuclear magnetic resonance (NMR), formation tester while drilling (FTWD), and imaging. Analyzing deep and ultra-deep resistivity inversions can also be used to evaluate permeability variations away from the wellbore which can affect the production profile. NMR can be used to estimate lateral permeability since the Timur-Coates model, usually used for carbonate reservoirs, honors both pore size and porosity variations. Mobility calculations obtained while drilling using formation tests are used to calibrate the Timur-Coates permeability equation. Fracture analysis based on high-resolution images can also be utilized to derive permeability. Integrating multiple sensors and after logging several wells, a reservoir-specific permeability model is developed based on unique field-specific parameters. The calibrated permeability model is then imported into completion design simulation software to design inflow control devices (ICDs). Hence, a higher confidence of lateral inflow equalization, water breakthrough delay and oil recovery maximization are achieved. The main objective of ICD is to maximize recovery by equalizing the inflow of different permeability compartments along the horizontal wellbore. Hence, permeability is a main controlling factor behind ICD design. Porosity-permeability transforms can overestimate or underestimate the permeability, especially in heterogenous carbonates. Integrating multiple LWD measurements provides improved understanding of lateral permeability changes enabling timely ICD design decisions to be taken. One of the main benefits of the customized calibrated permeability is a better prediction of simulated productivity index (PI), primarily affected by permeability profile input into completion design software and most influential in ICD design. While NMR, FTWD and imaging are sensitive to permeability variations near the wellbore, indications of formation characteristics in the far field can be indicated by analyzing deep and ultra-deep resistivity inversions. Integrating both measurements in the completions design can allow for better flow equalization and delay in the predicted water breakthrough. This paper presents an integrated workflow for enhanced permeability evaluation for a heterogeneous complex carbonate reservoir.