An Integrated Reservoir Modeling Case Study to Simulate Multi-Stage Hydraulically Fractured Horizontal Wells, based on Seismic, Petrophysical and Geological data for Pinedale Tight Gas Fluvial Reservoir
- M. Gaddipati (NITEC LLC) | T. Firincioglu (NITEC LLC) | E. LaBarre (ULTRA Petroleum) | Y. Yang (ULTRA Petroleum) | D. Wahl (ULTRA Petroleum) | P. Clarke (ULTRA Petroleum) | A. Long (ULTRA Petroleum) | C. Ozgen (NITEC LLC)
- Document ID
- Unconventional Resources Technology Conference
- SPE/AAPG/SEG Unconventional Resources Technology Conference, 20-22 July, Virtual
- Publication Date
- Document Type
- Conference Paper
- 2020. Unconventional Resources Technology Conference
- 26 in the last 30 days
- 26 since 2007
- Show more detail
|SPE Member Price:||USD 9.50|
|SPE Non-Member Price:||USD 28.00|
In recent years multi-stage fractured horizontal wells have become a norm in the development of unconventional oil and gas reservoirs. This paper focuses on reservoir modeling of the tight-gas sandstones in Pinedale Field, Green River Basin, Wyoming. This paper represents the first published literature to focus specifically on horizontal well performance in Pinedale. The objective of this study was to evaluate horizontal well productivity of the hydraulically fractured Lance Pool formation. Due to the fluvial nature of the formation and the complexity introduced by the hydraulic fracturing, an integrated workflow was developed utilizing a 3D simulation model combining seismic reflection, inversion, petrophysical and geological data.
A 3D facies model based on object-oriented geostatistical modeling was constructed using a combination of vertical lithology proportion curves (from vertical pilot wells) and reservoir net-to-gross (NTG) maps extracted from a deterministic seismic inversion volume. The NTG maps were honored during the geostatistical population of the fluvial sand bodies (sand generation model). The resultant facies model was then populated with petrophysical and geomechanical properties using the interpreted well logs. The final integrated model honors published characteristics for the Lance Formation. A dual-porosity reservoir simulation model was then utilized. The reservoir simulator integrated the hydraulic fracturing process, multi-phase flow and geomechanics in order to assess SRV generation during hydraulic fracturing and SRV geometry changes during production. The change in mean stress for each grid cell was implicitly solved with pressure and the other flow variables using poro-elastic information. The simulation model was calibrated to history match flow back and depletion periods including historical gas, oil (condensate) and water production rates together with the bottom hole pressure values.
A physics-based history matched simulation model was generated, including flow behavior for two wells in the study area. The hydraulic fractures created/propagated for sandstone and siltstone were tuned as history matching parameters. The calibrated model showed that major pressure depletion is limited to the sand channels due to ductility contrasts with the finer-grained facies. Predictive cases were modeled for 30- year EUR. The study refined our understanding of well performance drivers as related to advanced reservoir characterization, affording a robust prediction tool for undrilled locations.
The integrated reservoir modeling technology presented in this study is impactful as it solves for geomechanics and flow in a single process. The multi-well calibration of the model provides physics-based assessments of gas production from a complex reservoir, leveraging horizontal well technology. Predictive cases illustrate a quantitative performance characterization tool for decision making, including field optimization and development.
To include the all the complexities associated with the reservoir coupled with hydraulic fracturing of horizontal wells, this study required a thorough integration of different disciplines from geology, petrophysics, geophysics, geomechanics and engineering in building a 3D reservoir simulation model. All the available data from different disciplines was analyzed and integrated to a create a consistent physics-based model.
|File Size||3 MB||Number of Pages||17|