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Natural fractures can reactivate during hydraulic stimulation and interact with hydraulic fractures producing a complex and highly productive natural-hydraulic fracture network. This phenomenon and the quality of the resulting conductive reservoir area are primarily functions of the natural fracture network characteristics (e.g., spacing, height, length, number of fracture sets, orientation, and frictional properties); in situ stress state (e.g., stress anisotropy and magnitude); stimulation design parameters (e.g., pumping schedule, the type/volume of fluid[s], and proppant); well architecture (number and spacing of stages, perforation length, well orientation); and the physics of the natural-hydraulic fracture interaction (e.g., crossover, arrest, reactivation). Geomechanical models can quantify the impact of key parameters that control the extent and complexity of the conductive reservoir area, with implications to stimulation design and well optimization in the field. We have developed a series of geomechanical simulations to predict natural-hydraulic fracture interaction and the resulting fracture network in complex settings. A geomechanics-based sensitivity analysis was performed that integrated key reservoir-geomechanical parameters to forward model complex fracture network generation, synthetic microseismic (MS) response, and associated conductivity paths as they evolve during stimulation operations. The simulations tested two different natural-hydraulic fracture interaction scenarios and could generate synthetic MS events. The sensitivity analysis revealed that geomechanical models that involve complex fracture networks can be calibrated against MS data and can help to predict the reservoir response to stimulation and optimize the conductive reservoir area. We analyzed a field data set (obtained from two hydraulically fractured wells in the Barnett Formation, Tarrant County, Texas) and established a coupling between the geomechanics and MS within the framework of a 3D geologic model. This coupling provides a mechanics-based approach to (1) verify MS trends and anomalies in the field, (2) optimize conductive reservoir area for reservoir simulations, and (3) improve stimulation design on the current well in near-real-time and well design/stimulation for future wells.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe drilling industry is turning from the use of oil-based mud to environmentally sensitive water-based mud systems. However, highly conductive water-based mud tends to limit the effective dynamic range of induction instruments, such as the multi-component induction well logging tool (3DEX SM ).To illustrate the influence of the conductive borehole and invasion on the 3DEX logs, we performed theoretical simulations for a simple 2-D formation model.To expand the operational range of the 3DEX technology in a water-based mud environment, we propose logging the 3DEX tool in combination with galvanic tools (Dual Laterolog, DLL and Micro Laterolog, MLL, or array lateral log, HDLL, and MLL) and apply the following sequential data interpretation procedure:(1) Determine the formation resistivity structure of the near wellbore environment and the horizontal resistivity of the uncontaminated zone using the galvanic measurements,(2) Determine the vertical resistivity and formation resistivity anisotropy of the uncontaminated zone using the results of the previous step and the deep 3DEX measurements.Evaluation of this technology on a series of synthetic models allows us to outline the expanded 3DEX operational environment. The presented field example validates the technology.The conclusion is that the combination of galvanic and induction measurements along with an inversion-based data interpretation method can effectively extend the dynamic range of the 3DEX technology, allowing the use of this technology in wells drilled with conductive water-based mud systems.

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