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Collaborating Authors
Results
Innovative Modeling to Quantify the Impact of Natural Fractures, Optimize Well Spacing and Increase Productivity in the Marcellus Shale
Mohamed, Farid Reza (Schlumberger) | Otulana, Dolapo (Schlumberger) | Salazar, Ivan Alberto (Schlumberger) | Xue, Han (Schlumberger) | Fan, Li (Schlumberger) | Shan, Dan (Sensia, LLC) | Bennett, Jim (JLB Geo Consulting, LLC) | Abubakar, Kabiru (Independent) | Barrie, Kyle (Rees-Jones Holdings, LLC) | Yeager, Bryce (Independent) | Simpson, Marcia (Steel Roots Ventures, LLC) | Jenkins, Creties (Rose and Associates)
Abstract Individual well performance in the Marcellus Shale of northeastern Pennsylvania varies markedly, even in areas where the lithology, fluid composition, and completion design are consistent. A primary reason for this is the natural fracture system, which influences hydraulic fracture growth, dynamic fluid flow, reservoir pressure and stress behavior. Chief Oil and Gas (Chief) contracted Schlumberger to conduct an integrated study using an innovative modeling approach to quantify the impact of these natural fractures and optimize field development. Working together, the team created an approach that consisted of constructing and coupling three models: a 3D geomechanical model, an unconventional fracture model (UFM), and a 3D dynamic dual-porosity model. The geomechanical model is composed of a discrete fracture network (DFN) containing both regional (J1 and J2 sets) and tectonic fractures. These are interpreted from seismic attributes (anisotropy azimuth, seismic velocity anisotropy) and ant tracking. The UFM model simulates the growth of hydraulic fractures and their interaction with natural fractures in the DFN. Portions of the natural fracture network are assumed to be open tectonic fractures, and their flow properties are adjusted (porosity and permeability) to match well performance. Adjustments are also made to account for production-related perturbations in dynamic stress magnitude and azimuth, which impact later wells. These modifications to the fracture network are critical for history matching the dual-porosity model. The production history match showed that hydraulic fractures and open tectonic natural fractures are key production drivers in the study area, and that the spatial variability of the natural fracture network exerts more influence on well performance than initially thought. The connection between the hydraulic fracture network and portions of the open tectonic natural fracture system enhances parent well access to larger drainage areas. This controls the strongly variable well production observed in the study area. Subsequent stress perturbation resulting from parent well depletion is detrimental to the completion efficiency of the child wells, even even though they have better frac designs with higher proppant loading. The modeling work also shows that the gas-in-place is consistent with volumetric and rate transient analysis (RTA) estimates. The coupling of the three models reasonably approximated changing reservoir conditions and created a nexus of domain expertise including geology, geophysics, geomechanics, stimulation, completions engineering and reservoir engineering. This enabled an understanding of the complex reservoir behavior of the naturally-fractured Marcellus Shale and generation of an optimized fit-for-purpose development plan. Chief was already implementing changes in spacing and increasing the distance between offset PDP (Proved Developed Producing) wells and this study affirmed that revised development plan.
- North America > United States > West Virginia (1.00)
- North America > United States > Virginia (1.00)
- North America > United States > Pennsylvania (1.00)
- (3 more...)
- Geology > Structural Geology > Tectonics (1.00)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.83)
- Geology > Petroleum Play Type > Unconventional Play > Shale Play > Shale Gas Play (0.81)
Integration of Core Analysis, Pumping Schedule and Microseismicity to Reduce Uncertainties of Production Performance of Complex Fracture Networks for Multi-Stage Hydraulically Fractured Reservoirs
Niu, Geng (Texas A&M University) | Sun, Jianlei (Texas A&M University) | Parsegov, Sergei (Texas A&M University) | Schechter, David (Texas A&M University)
Abstract Microseismicity is a physical phenomenon which allows us to estimate the production capability of the well after hydraulic fracturing (HF) in a naturally fractured (NF) reservoir. Some of the microseismic events are reactivations of NFs induced by a direct hit of HF, while others are induced by the fluid leak-off from the previous stages or by elastic waves emitted into the reservoir with hydraulic fracture plane propagation. The former NFs have a chance to be propped there as the latter will not significantly increase their contribution to the production. Identification of such microseismic events helps to reduce uncertainty in the description of fracture network geometry. Based on inferred data from core analysis NF densities and orientations, we generated multiple realizations of the semi-stochastic Discrete Fracture Network (DFN). In order to constrain them, we used time evolution of microseismic cloud in addition to results of core analysis. Fluid and proppant pumping schedule is used to identify such microseismic events because they should be located close to the pressure diffusion front generated by hydraulic fluid. Events outside of proposed region may be triggered by other factors, such as stress-strain relaxation from other stages and correspondent fractures. In most cases, they are not wide enough to take proppant from the main HF. This approach was used to reduce range of production for DFN realizations. This workflow is implanted to a 15-stage hydraulic fracture treatment on a horizontal well placed in a siltstone reservoir with intrinsic fractures. The spatio-temporal dynamics of microseismic events are classified into two groups by the front of nonlinear pressure diffusion caused by 3-dimensional hydraulic fracturing, considered as effective and ineffective events. DFNs with only effective microseismicity and with all the induced events are generated. Then, two types of DFN related uncertainties on production are performed to evaluate the impact of filtration. Results of aleatory uncertainty quantification caused by the randomness of DFN modeling indicate the filtered events can generate a production DFN with a more consistent connected fracture area. Moreover, sensitivity analysis caused by lack of accuracy in natural fracture characterization shows the production area of DFN with filtration process is more insensitive to the variation of fracture parameters. Finally, a history match with production data and pressure data indicates this DFN model properly represents the reservoir and completion. Our methodology characterizes well the conductive fracture network utilizing core data, microseismic data, and pumping schedule. It could restore the true productivity of each fractured stage from a massive microseismic cloud, which helps understand the contribution of fracturing job right after the treatment.
- Asia (1.00)
- North America > United States > Texas > Midland County (0.29)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.66)
- North America > United States > West Virginia > Appalachian Basin > Marcellus Shale Formation (0.99)
- North America > United States > Virginia > Appalachian Basin > Marcellus Shale Formation (0.99)
- North America > United States > Texas > West Gulf Coast Tertiary Basin > Eagle Ford Shale Formation (0.99)
- (33 more...)
- Information Technology > Modeling & Simulation (0.46)
- Information Technology > Communications > Networks > Sensor Networks (0.46)