Quantifying Capital Efficiency with Integrated Well Simulation

Optimization of unconventional well performance is often limited by segmented workflows across completions, reservoir engineering, and development planning. While changes in completion design may improve production outcomes, linking these changes to quantifiable economic results typically requires iterative, cross-disciplinary analysis. This separation can slow decision-making and obscure which technical parameters most strongly influence capital efficiency.
 
This study applies an integrated simulation framework that combines completion design parameters, reservoir modeling outputs, and economic assumptions within the PrePad modeling environment for a Montney asset. The workflow integrates key completion variables with type curves and productivity scaling factors, along with asset-level economic inputs such as commodity price assumptions, operating expenses, capital cost estimates, and royalty structures. Consolidating these elements into a single analytical framework allows concurrent evaluation of design, production, and economic outcomes.
 
A structured multi-variable parameter sweep is performed across sand loading, clusters per stage, and cluster spacing. For each design scenario, the model estimates completion duration and capital cost impacts, generates a production forecast using representative type curves, and calculates standard financial indicators, including net present value (NPV) and payback period.
 
Results indicate that, within the evaluated parameter range, a ~30% increase in sand loading produces an approximate ~20% increase in per-well NPV. This improvement corresponds to an incremental $400–$600 thousand per well in early-life free cash flow and a 5–9% increase in estimated ultimate recovery (EUR). In contrast, variations in clusters per stage and cluster spacing demonstrate comparatively lower economic sensitivity, indicating that sand loading is the dominant value driver within the bounds of this analysis.