Skip to main navigation Skip to search Skip to main content

Impact on drained rock volume (DRV) of storativity and enhanced permeability in naturally fractured reservoirs: Upscaled field case from hydraulic fracturing test site (HFTS), Wolfcamp Formation, Midland Basin, West Texas

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Hydraulic fracturing for economic production from unconventional reservoirs is subject to many subsurface uncertainties. One such uncertainty is the impact of natural fractures in the vicinity of hydraulic fractures in the reservoir on flow and thus the actual drained rock volume (DRV). We delineate three fundamental processes by which natural fractures can impact flow. Two of these mechanisms are due to the possibility of natural fracture networks to possess (i) enhanced permeability and (ii) enhanced storativity. A systematic approach was used to model the effects of these two mechanisms on flow patterns and drained regions in the reservoir. A third mechanism by which natural fractures may impact reservoir flow is by the reactivation of natural fractures that become extensions of the hydraulic fracture network. The DRV for all three mechanisms can be modeled in flow simulations based on Complex Analysis Methods (CAM), which offer infinite resolution down to a micro-fracture scale, and is thus complementary to numerical simulation methods. In addition to synthetic models, reservoir and natural fracture data from the Hydraulic Fracturing Test Site (Wolfcamp Formation, Midland Basin) were used to determine the real-world impact of natural fractures on drainage patterns in the reservoir. The spatial location and variability in the DRV was more influenced by the natural fracture enhanced permeability than enhanced storativity (related to enhanced porosity). A Carman-Kozeny correlation was used to relate porosity and permeability in the natural fractures. Our study introduces a groundbreaking upscaling procedure for flows with a high number of natural fractures, by combining object-based and flow-based upscaling methods. A key insight is that channeling of flow through natural fractures left undrained areas in the matrix between the fractures. The flow models presented in this study can be implemented to make quick and informed decisions regarding where any undrained volume occurs, which can then be targeted for refracturing. With the method outlined in our study, one can determine the impact and influence of natural fracture sets on the actual drained volume and where the drainage is focused. The DRV analysis of naturally fractured reservoirs will help to better determine the optimum hydraulic fracture design and well spacing to achieve the most efficient recovery rates.

Original languageEnglish
Article number3852
JournalEnergies
Volume12
Issue number20
DOIs
StatePublished - 12 Oct 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Keywords

  • Drained rock volume
  • Enhanced permeability
  • Flow modeling
  • Fracture porosity
  • Hydraulic fractures
  • Hydraulic fracturing
  • Hydraulic fracturing test site
  • Midland basin
  • Natural fractures
  • Naturally fractured reservoirs
  • Particle paths
  • Time of flight
  • Wolfcamp formation

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Impact on drained rock volume (DRV) of storativity and enhanced permeability in naturally fractured reservoirs: Upscaled field case from hydraulic fracturing test site (HFTS), Wolfcamp Formation, Midland Basin, West Texas'. Together they form a unique fingerprint.

Cite this