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Al Nouf Field in ADNOC

Overview

ADNOC’s WAG injection operations required validation of CRM connectivity analysis against full-physics forecasts. A key challenge was that simulation forecasts often start from a BHP-controlled state rather than the field’s true operational regime, leading to unrealistic production trends and limiting the reliability of direct well-by-well comparisons.

Objective

  • Align CRM-based injector–producer connectivity insights with simulation forecasts.
  • Identify Efficient Producers that show response to changes in injection strategy.
  • Develop a workflow for realistic, physics-consistent comparison between CRM and simulation results.

Approach

1

Define True Efficient Producers

Wells whose production changes significantly when injection rates are adjusted, determined through simulation sensitivity analysis.

Validation Workflow

  • Step 1: Run CRM with historical injectors and optimized injection plan.
  • Step 2: Run simulation with the same groupings and fixed-rate forecast starting from realistic operational states.
  • Step 3: Compare field-level directional trends, not per-well exact matches, to account for differences in control logic and lag.
2

Cross-Match Analysis

Identify wells classified as efficient in both CRM and simulation to confirm robustness of connectivity results.

Key Advantages

Physics-Consistent Comparison

Ensures that starting conditions and trends in simulation forecasts match realistic field behavior.

Unified Validation Criteria

Combines CRM’s data-driven connectivity with simulation’s modeling to improve confidence in injection optimization decisions.

Targeted Optimization

Focuses on wells that truly respond to injection changes, avoiding CAPEX on low-impact producers.

Results

Identified regions using hybrid models where gas was going into the gas cap.
Out of 53 WAG injectors, 5 efficient producers were consistently identified by both CRM and simulation.
Mapped injector–producer connections to guide targeted optimization.
A repeatable validation workflow for future CRM–simulation cross-checks.

Impact

"This work established a robust alignment process between data-driven CRM insights and full-physics simulation outputs. The approach enables ADNOC to confidently prioritize injection changes, improve WAG efficiency, and focus operational resources on wells with the highest production response potential."