Hydraulic fracturing for improved nutrient delivery in microbially-enhanced coalbed-methane (MECBM) production

Sheng Zhi, Derek Elsworth, Jiehao Wang, Quan Gan, Shimin Liu

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Microbially enhanced coalbed methane (MECBM) recovery is a novel method to increase gas production by injecting nutrients, either with/without microorganisms, in depleted CBM wells. However, to be effective, methanogens require that the nutrient must be delivered efficiently by aqueous solution to a maximally large reservoir volume for microbial colonization. This study seeks to improve understanding of solute transport and microbial gas generation in naturally fractured reservoirs that are both pristine and hydraulically fractured. We complete a field-scale numerical simulation using an equivalent multi-continuum method to define the effectiveness of nutrient delivery. The complex pre-existing fracture pattern in the coalbed is represented by an overprinted discrete fracture network (DFN) to capture the natural heterogeneity and anisotropy of fracture permeability. A simplified PKN model is adopted to simulate hydraulic fracture propagation based on linear elastic fracture mechanics (LEFM). The hydraulically stimulated case is compared to the untreated control case, both without and with a network of natural fractures. Saturated cleat area, cumulative injection volume and prediction of methane yields are systematically modeled and analyzed for all three cases. We show that hydraulically stimulated fracture pathways, especially when connecting with a natural fracture network, optimally deliver nutrient remotely from the injection well, thereby increasing nutrient delivery and improving methane production and potential recovery. However, large magnitudes of proppant embedment and related permeability loss in the hydraulic fractures may reduce MECBM recovery. In the optimal production scenario, the methane production rate may reach 31 ft3/ton, an approximately 5-fold increase over that from the pristine unstimulated case.

Original languageEnglish (US)
Pages (from-to)294-311
Number of pages18
JournalJournal of Natural Gas Science and Engineering
Volume60
DOIs
StatePublished - Dec 2018

All Science Journal Classification (ASJC) codes

  • Fuel Technology
  • Geotechnical Engineering and Engineering Geology
  • Energy Engineering and Power Technology

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