Deep Subsurface Oil Reservoirs as Poly-extreme Habitats for Microbial Life. A Current Review

Abstract

AbstractOil reservoirs located deep within the earth crust represent one of the most challenging environments for life, usually providing combinations of high temperatures and pressures, as well as high concentrations of salts, heavy metals, and organic solvents. Organisms thriving in such environments, therefore, have to be truly poly-extremophiles, adapted to conditions otherwise very hostile to life. In spite of this, research carried out in many groups worldwide throughout the past decades has revealed that deep subsurface oil reservoirs indeed are populated by diverse consortia of poly-extremophilic Bacteria and Archaea. Numerous sites on all continents have been sampled in search for novel species and strains to describe and compare microbial consortia and to understand biological processes that might occur in response to and possibly interfere with an efficient oil production. In addition, the special adaptations of oil reservoir microbes to their extreme environments have rendered them highly attractive for bioprospecting approaches for novel enzymes and metabolites with potential industrial value.In this chapter, we provide a current status overview of subsurface oil reservoir microbiology research, covering sites with in situ temperatures of 50 °C and higher. We also discuss the challenge of representative sampling and contamination issues affecting research results and derived conclusions. Further, the current understanding of metabolic capabilities predominant in oil reservoir communities is discussed, including the challenges these communities provide in oil production and their potential with respect to Biologically activated Enhanced Oil Recovery (Bio-EOR) and other industrial applications.KeywordsMicrobial ConsortiumIntellectual Property RightFermentative BacteriumalkB GeneReservoir SiteThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.