Investigating the Effect of Improved Fracture Conductivity on Production Performance of Hydraulically Fractured Wells: Field-Case Studies and Numerical Simulations

Abstract

Unconventional reservoirs require extensive hydraulic-fracturing treatments to produce fluids economically and efficiently. The main purpose of such treatments is to create complex fracture networks with high-conductivity paths deeper into the nonstimulated reservoir regions. Proppants play an important role in maintaining good-quality fracture conductivities, which then greatly affect long-term production performance. In addition, research on proppants has shown a reduction in conductivities under downhole stresses and multiphase-flow behaviours. Therefore, it is important to study the effect different proppants and conductivities have on production performance through actual field cases.To evaluate the production performance of wells completed with different proppants, the authors proposed an integrated work flow for characterization and simulation of unconventional reservoirs. This work flow is unique because of the stochastic fracturenetwork-generation algorithms and improved unstructured-gridgeneration techniques. Both analysis of field-production data and numerical simulations were performed on eight wells in the CAPA field of North Dakota. For the field-data analysis, three public-data resources were reviewed to prepare a summary of reservoir properties, fracture properties, proppant properties, and production history. For the numerical simulations, all the wells were modelled and simulated with the proposed work flow. Finally, sensitivity analyses were carried out to investigate the effects of fracture conductivities and natural fractures.After completing the field-case studies and reservoir simulations, it was concluded that with the same fracture design, higher fracture conductivity improves production performance. Pumping a smaller volume of upgraded proppants with higher conductivity not only improves long-term production performance, but also justifies the additional costs and reduces the overall operation time of the entire hydraulic-fracturing job. The stimulated reservoir volume was greatly increased, as was the production performance, where natural fractures exist.In this paper, field-data analysis was applied in the Bakken to demonstrate the integrated unconventional work flow. The proposed unstructured-gridding algorithms can be incorporated into any preprocessor to handle complex networks. Reservoir, fracture, and proppant characterization and reservoir simulation of the field cases can help engineers prepare and interpret simulation input and output.

A Comprehensive Model for Real Gas Transport in Shale Formations with Complex Non-planar Fracture Networks

“…According to recent EIA report, 43 billion cubic feet of gas per day is produced from shales in the US1. Hydraulic fracturing in shale formations is often associated with complex fracture networks23456. The occurrence of complex non-planar fracture network is much more common than initially anticipated, especially in unconventional reservoirs6.…”

Shale Reservoir Drainage Visualized for a Wolfcamp Well (Midland Basin, West Texas, USA)

“…Another shortcoming is that such Cartesian grids cannot effectively represent complex and non-planar fracture networks. The latter can be better captured using unstructured grids to define Voronoi cells [29,45,46]. Some gains in computational time can be achieved using coarse scale parameters from numerical homogenization to upscale the non-transient regions in the reservoir model [47].…”

Efficient Development Method for High-Viscosity, Complex Fault-Block Reservoir

“…In the present study, there exist a number of investigation on injection pipeline and measurement and adjustment technology, but few on segment number determination, layer combination way and water injection quantity optimization for each segment (Wang 2012;Sun 2015aSun , 2015b. Yuan (2006) applied SVM (Support Vector Machine) method on water injection technology, and the effect prediction model was established.…”