Driven by field logistics in an unconventional setting, a well may undergo weeks to months of shut-in after hydraulic-fracture stimulation. In unconventional reservoirs, field experiences indicate that such shut-in episodes may improve well productivity significantly while reducing water production. Multiphase-flow mechanisms were found to explain this behavior. Aided by laboratory relative permeability and capillary pressure data, and their dependency on stress in a shale-gas reservoir, the flow-simulation model was able to reproduce the suspected water-blocking behavior. Results demonstrate that a well-resting period improves early productivity and reduces water production. The results also indicate that minimizing water invasion in the formation is crucial to avoid significant water blockage. Water-Block Description and RemediationMultiphase-Flow Mechanisms. Scanning-electron-microscope (SEM) analysis of a core sample shows that two types of pores

The interpretation of microseismic data was initially focused on hydraulic fracture length and height, providing an important measurement to calibrate planar fracture propagation models. However, microseismic data in the Barnett shale exhibited significantly more complex patterns compared to typical tight-gas sands. The concept of stimulated reservoir volume (SRV) was developed to provide some quantitative measure of stimulation effectiveness in the Barnett shale based on the size of the microseismic "cloud." SRV is now ubiquitous when discussing well performance and stimulation effectiveness in unconventional reservoirs. However, SRV and similar techniques provide little insight into two critical parameters: hydraulic fracture area and conductivity. Each of these can vary significantly based on geologic conditions and fracture treatment design. Hydraulic fracture area and fracture conductivity, combined with reservoir permeability, stress regime, and rock properties, control well performance, not SRV.The concept of SRV has spawned numerous reservoir engineering models to approximate the production mechanisms associated with complex hydraulic fractures and to facilitate production modeling and well performance evaluations (e.g., rate transient analysis). However, these reservoir engineering models are often divorced from the fracture mechanics that created the fracture network, a significant limitation when evaluating completion effectiveness. Additionally, the interpretation of the microseismic data and the calculation of SRV are poorly linked to the actual hydraulic fracture geometry and distribution of fracture conductivity. This paper presents detailed numerical reservoir simulations coupled with hydraulic fracture modeling that illustrates the limitations and potential misapplications of the SRV concept. This work shows that simplifying assumptions in many SRVbased rate transient models may lead to estimates of hydraulic fracture length and reservoir permeability that are not well suited for completion optimization. Two case histories are presented that illustrate the limitations of SRV-based well performance evaluations. The paper concludes that using microseismic images to estimate a SRV may not be sufficient for completion evaluation and optimization. However, the simple calculation of microseismic volume (MV) can provide significant insights to guide fracture and reservoir modeling endeavors.

Some shale gas and oil wells undergo month-long shut-in times after multi-stage hydraulic fracturing well stimulation. Field data indicate that in some wells, such shut-in episodes surprisingly increase the gas and oil flow rate. In this paper, we report a numerical simulation study that supports such observations and provides a potentially viable underlying imbibition and drainage mechanism. In the simulation, the shale reservoir is represented by a triple-porosity fracture-matrix model, where the fracture forms a continuum of interconnected network created during the well simulation while the organic and non-organic matrices are embedded in the fracture continuum. The effect of matrix wettability, capillary pressure, relative permeability, and osmotic pressure, that is, chemical potential characteristics are included in the model.The simulation results indicate that the early lower flow rates are the result of obstructed fracture network due to high water saturation. This means that the injected fracturing fluid fills such fractures and blocks early gas or oil flow. Allowing time for the gravity drainage and imbibition of injected fluid in the fracture-matrix network is the key to improving the hydrocarbon flow rate during the shut-in period.

Driven by field logistics in an unconventional setting, a well may undergo weeks to months of shut-in following hydraulicfracture stimulation. In unconventional reservoirs, field experiences indicate that such shut-in episodes may improve well productivity significantly while reducing water production. Multiphase flow mechanisms were found to explain this behavior. Aided by laboratory relative-permeability, capillary pressure data, and their dependency to stress in a shale-gas reservoir, the flow-simulation model was able to reproduce the suspected water blocking behavior. Results demonstrate that a well resting period improves early productivity while reducing water production. The results also indicate that minimizing water invasion in the formation is crucial to avoid significant water blockage.

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.