Abstract

A two-mile lateral infill well was drilled roughly 2000 ft from an offset producer in the same formation. The offset producer was a one-mile lateral and ran parallel to the heel portion of the child. The objective was to maximize productivity and completion efficiency by completing the infill well in a geo-informed manner. This would be accomplished by isolating depleted regions, maximizing cluster efficiency, decreasing the required stage count, and utilizing a practical treatment approach to maximize stimulation in the depleted and non-depleted sections of the wellbore. The authors utilized the geomechanics of the infill well, a depletion analysis, limited entry modeling, and hydraulic fracture modeling to optimize the child well’s completion approach.

The optimization workflow applied to the infill lateral was as follows:

1. Derive a high resolution geomechanical and pore pressure profile from at-the-drill bit vibration data

2. Evaluate the min. horizontal stress (Shmin) changes along the lateral to optimize stage placement, stage length, and limited entry strategy

3. Utilize a hydraulic fracture model to simulate practical "what-if" scenarios to optimize hydraulic fracture flowing area in the depleted and non-depleted stages

4. Apply the optimal stage and treatment design in the field

After the well was completed, the treatment data were evaluated against the geomechanics and pore pressure predictions using analytics software. After 12 months of production, the production data of the child well was evaluated against a nearby legacy producer.

Compared to a base geometric design, the stage count was reduced by 8 (19%), total entry points and cluster efficiency remained the same, and the average stage Shmin variability was reduced by over 80%. Based on modeling results and practicality, treatment volume was reduced in depleted stages by 25% and increased in non-depleted stages by 25%. The design was successfully implemented in the field.

After completion, the stage pressure data recorded during stimulation were analyzed against the stage-aggregated geomechanics and pore pressure data with good results.

The subject well is a strong producer when compared to its peers. Its oil and gas production has outperformed a nearby legacy two-mile lateral well by 36% after 12 months.

As infill development becomes the norm, subsurface data should at a minimum be considered and at best be integrated in optimization workflows to address challenges. The geomechanical data included in this study are economically obtained and operationally non-intrusive. In addition, the derived pore pressure profile uniquely identifies discrete regions of depletion along the near-wellbore allowing for stage and cluster level changes. Finally, the authors successfully implemented a pre-completion optimization workflow that can be explored in other unconventional reservoirs where fracture-driven interaction causes and reservoir drainage mechanisms vary widely.

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