Diagnostic fracture injection tests (DFIT) are commonly used to characterize stress and reservoir properties in unconventional reservoirs. Although simple in concept, interpreting DFIT results can be difficult because several factors can cause results to deviate from ideal DFIT behavior. Some examples of nonideal DFIT behavior include steep pressure declines after shut-in, absence of pseudolinear and pseudoradial flow, and excessive storage indications. Such deviations from ideal DFIT behavior challenge our ability to estimate formation properties reliably. Potential drivers of nonideal behavior include heterogeneous rock properties, complex rock/fluid interaction, thermal effects, phase entry, and natural fractures.
The objective of this study is to investigate how these factors can impact DFIT results and interpretations. A comprehensive approach was taken using a combination of pressure transient analysis, frac modeling, analytical leakoff modeling, and detailed numerical simulation of DFIT behavior. The application was for a horizontal well, completed in a shale gas reservoir, which included an actual field DFIT. Detailed modeling included full wellbore transients and storage, hydraulic behavior through induced fractures, as well as complex interactions between rock, fluids, and natural fractures. It was determined that the actual DFIT showed indications of a complex network created by the pump-in. Closure pressure estimates were found to be reliable, between the simulation cases and DFIT analysis. However, a consistency check on initial reservoir pressure had to be used to obtain reasonable estimates compared to the simulation input. Finally, estimates of reservoir conductivity were highly uncertain compared to the actual simulation inputs. Furthermore, the actual DFIT estimates of reservoir pressure and conductivity were found to be overoptimistic. Estimated ultimate recovery using DFIT-based estimates of reservoir quality was shown to be more than twice the estimated ulterimate recovery using reservoir quality estimates made with integrated core, log, and a pressure build-up test.