Next generation modeling of microbial souring – Parameterization through genomic information

Yiwei Cheng, Christopher G. Hubbard, Liange Zheng, Bhavna Arora, Li Li, Ulas Karaoz, Jonathan Ajo-Franklin, Nicholas J. Bouskill

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Biogenesis of hydrogen sulfide (H2S) (microbial souring) has detrimental impacts on oil production operations and can cause health and safety problems. Understanding the processes that control the rates and patterns of sulfate reduction is crucial in developing a predictive understanding of reservoir souring and associated mitigation processes. This work demonstrates an approach to utilize genomic information to constrain the biological parameters needed for modeling souring, providing a pathway for using microbial data derived from oil reservoir studies. Minimum generation times were calculated based on codon usage bias and optimal growth temperatures based on the frequency of amino acids. We show how these derived parameters can be used in a simplified multiphase reactive transport model by simulating the injection of cold (30 °C) seawater into a 70 °C reservoir, modeling the shift in sulfate reducing microorganisms (SRM) community composition, sulfate and sulfide concentrations through time and space. Finally, we explore the question of necessary model complexity by comparing results using different numbers of SRM. Simulations showed that the kinetics of a SRM community consisting of twenty-five SRM could be adequately represented by a reduced community consisting of nine SRM with parameter values derived from the mean and standard deviations of the original SRM.

Original languageEnglish (US)
Pages (from-to)189-203
Number of pages15
JournalInternational Biodeterioration and Biodegradation
Volume126
DOIs
StatePublished - Jan 1 2018

Fingerprint

Parameterization
Sulfates
parameterization
genomics
Microorganisms
sulfate
microorganism
modeling
Oils
Oil and Gas Fields
Hydrogen Sulfide
reactive transport
generation time
Seawater
Hydrogen sulfide
Growth temperature
Sulfides
hydrogen sulfide
health and safety
Codon

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Biomaterials
  • Waste Management and Disposal

Cite this

Cheng, Yiwei ; Hubbard, Christopher G. ; Zheng, Liange ; Arora, Bhavna ; Li, Li ; Karaoz, Ulas ; Ajo-Franklin, Jonathan ; Bouskill, Nicholas J. / Next generation modeling of microbial souring – Parameterization through genomic information. In: International Biodeterioration and Biodegradation. 2018 ; Vol. 126. pp. 189-203.
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Next generation modeling of microbial souring – Parameterization through genomic information. / Cheng, Yiwei; Hubbard, Christopher G.; Zheng, Liange; Arora, Bhavna; Li, Li; Karaoz, Ulas; Ajo-Franklin, Jonathan; Bouskill, Nicholas J.

In: International Biodeterioration and Biodegradation, Vol. 126, 01.01.2018, p. 189-203.

Research output: Contribution to journalArticle

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