We are now a few years into the surge of a new generation of geoscientists tasked with filling a huge gap in petrotechnical professionals and expertise. This long-awaited demographic change was a correction to years of uncertainty, cyclical economics, and competitive economics, which saw the oil and gas industry falling short in attracting students towards a professional career in the geosciences. While this demographic change is greatly welcomed, it is not without its challenges.
Unlike the previous population surge of the 1970s and 1980s, where geoscientists were exposed to extensive training and mentoring on the fundamentals of a broad range of exploration and development disciplines, this new generation comes into the industry in an era where specialization is the norm, mentoring resources are limited, and exploration and development technical problems are routinely and acutely challenging.
Oil companies, service companies, and professional societies are addressing this educational gap with a careful balance of expert mentoring, classroom training, and applied geoscience training against the rigorous schedules and deadlines of day-to-day activities that drive a company's business. However, all too often when we speak of equipping this next generation of geoscientists with software technology, we speak of equipping them with 70% or 80% solutions. While these solutions may address deployment and information technology challenges, intuitively, this characterization is a downgrade in requirements directly in conflict with the challenges facing the oil and gas industry, namely, replacing reserves and understanding and reversing production declines.
This next generation of geoscientists requires and deserves technology that fully contemplates the dependencies of the sciences that are the foundations of the problems that we are trying to resolve. These dependencies are encapsulated in the names of the sciences (e.g. geophysics, geochemistry, geomodeling, petrophysics, rock physics) that we routinely deploy in the search for and exploitation of hydrocarbons. When these dependencies are properly engineered into software applications, geoscientists are able to elevate the quality of their work and insights into the subsurface.
Today, a proper understanding of the types and sources of anisotropy (velocity dependence on azimuth) can have a huge impact on the quality of the seismic image and the interpretation of that image. Here, the fabric and orientation of the geology governs the physics of wave propagation, which in turn governs the integrity of the seismic image and the comprehensiveness of information that can be extracted from the seismic method. Technologies that not only consider these dependencies but implement them for convenient access by this next generation of geoscientists exist today.
Seventy to 80% geomodeling solutions, while addressing convenience and ease of use, generally cannot be carried out without significant compromises in geologic data and geologic integrity. Cleary, this new generation of geoscientists should be schooled in generating geologic models without approximations or deformations induced by the "fitting" of cells to an inadequate geologic framework. Today, solutions that incorporate sound geologic rules and mathematics into the fabric of geomodeling software exist and should be the foundation of this generation of geoscientists' toolkit.
For many of us who belong to the population surge of the 1970s and 1980s, a 70% outcome was considered substandard and an 80% outcome was considered an average one. The oil industry and the next generation of geoscientists deserve better than this.
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