Completion Optimization Under Constraints: An Eagle Ford Shale Case Study

Abstract

The Eagle Ford shale (EFS) is the largest single economic development in the history of the state of Texas and ranks as the largest oil and gas development in the world on the basis of capital invested. Between 2008 and the present, the EFS has become one of the most heavily drilled rock units in the US and is the most-active shale play in the world.

This paper presents a completion-optimization framework for unconventional plays. The framework uses well-production performance analysis to estimate the fracture characteristics, and assists in diagnosing potential low-productivity issues. The framework enables precompletion planning, real-time completion operations monitoring, and post-completion evaluation of the design effectiveness, and it optimizes future designs.

The key components of the framework are prospectivity analysis, completions optimization, and well-performance analysis. Prospectivity analysis provides the map of reservoir quality and rock quality across the play. Precompletion planning, a component of completions optimization, is driven by prospectivity analysis with the goal to design the best completion on the basis of the rock-quality data available. During completions monitoring, the designs are updated on the basis of the actual field pump rates and quantities of proppant pumped to estimate actual hydraulic- and propped-fracture characteristics. The effective fracture geometry is determined on the basis of well-production calibration. Wellbore and completion problems could be diagnosed in this analysis, including damage of fractures, fluid behavior, and well interference.

We applied this framework to wells completed in the EFS. The reservoir-quality variability is based on petrophysical evaluation of logs acquired on all study wells. The characteristics of propped fractures were estimated on the basis of geomechanical modeling of actual field pumping measurements. Even though the fractures extended above and below the target interval of the EFS, they were successful in creating the desired half-length from a design point of view. It was also observed that not all the clusters matured, because of the stress-shadow effect. The produced fluids in these wells ranged from black oil to gas condensate. Well interference was observed as a production penalty factor in well-performance analysis. The behavior of current wells was used to design optimal completions for wells that were planned to be completed.

This framework uses common data sets collected by a majority of operators. It provides intelligence for completion optimization of future wells after thorough investigation into fracture design, completion operation, and effective fracture characteristics. It is a systematic approach to optimized single-well design and field development (multiple wells, pad drilling).