The objective of hydraulic fracturing is to design and execute a fracture stimulation that achieves the desired fracture dimensions (length & conductivity) to maximize well productivity and reserve recovery. In order to truly achieve this objective information from the geosciences and engineering disciplines are required.
Geologic, geophysical, and petrophysical data are needed to understand reservoir quality, thickness, and extent. Reservoir engineering data is used to assess in-place hydrocarbons, flow capacity, permeability, and reservoir drainage area. Production decline analysis is used to assess reserve recovery and corroborate in-place hydrocarbons and flow capacity. Rock mechanics is used to assess the elastic properties of the formation of interest, bounding sediments, as well as the fracture mechanics. Finally, completion and stimulation engineering are used to design, execute, and evaluate the hydraulic fracture treatment. All of these data and disciplines are needed to truly optimize the fracture stimulations, production rate, and reserve recovery.
In recent years, there has been much discussion regarding the causes for, or reasons that the dimensions of the hydraulic fracture are shorter and less conductive than desired. These causes include: relative permeability effects1 , fracture fluid cleanup2-5 and gel damage6-12 , multi-phase and non-Darcy flow13-15 . In addition, reservoir heterogeneities, layering, and boundaries can result in less than optimal dimensions as well. These effects have been investigated; however, without the integration of quality multi-discipline data determining the inter-relationship or causal relationships of these effects is difficult. As a result, the factors truly affecting the fracture dimensions may be misinterpreted or misrepresented resulting in less than optimal results.
This paper will document a multi-discipline investigation of a multi-well South Texas Wilcox Field used to improve and optimize hydraulic fracture treatments in the area. The integration of this dataset will be used to determine fracture dimensions and assess the critical parameters for the creation of optimum fracture dimensions.