The evolution of energy

Geoscience Analytics from Pencils to Principal

By Bryn Davies
Wolfcamp A

It was not uncommon for a day in the life of a geoscientist to consist of printing rasters, constantly sharpening pencil crayons, hunched over a drafting table, while hand contouring maps.

Although these workflows are essential to the successful planning and drilling of a well, they were extremely time consuming. Additionally, the process often relied on niche skills, limiting communication and decision-making across teams.

Technological progress has vastly improved geoscientists’ workflows. Advanced geology and geophysics software can automate and create digital processes for the tasks listed above, in addition to building detailed visualizations that previously could only be contained in a geoscientist’s imagination. The rapid acceleration of computing processes has also empowered our geologists to analyze well logs, integrate seismic data and pick tops and publishing maps at a scale and frequency not imagined before.

As the industry evolved, so did the geologists’ workflows. Today, geologists are increasingly required to analyze massive amounts of data, and maybe even more importantly, communicate their interpretations, worth millions of dollars, to a broader multidisciplinary team. Working at scale in a viable and reliable way requires the application of data science techniques at almost every step of the workflow to produce consistent and repeatable results they can trust. When the subsurface interpretations are in a fully integrated software platform, our geologists can work seamlessly with our engineers, analysts and technologists to drive an increase in the quality and number of problems solved.

Understandably, the shift to applying emerging technologies and processes to subsurface analysis has been rapid, and many companies may be reluctant to adopt such technologies. That said, data science has rocked our world, from improving the quality of LAS data to scaling rock properties and predicting missing data in data sets. Geologists were once limited by human processing time and spent days drawing maps; now, they are limited only by their ability to keep up with innovative ways to solve subsurface problems.

Figure 1 | Manual mapping processes in separate G&G software, not dynamic, hard to update, slow to make, less diagnostic / prescriptive interpretations possible with well productivity trends and subsurface analysis
Wolfcamp B
Wolfcamp C
Figure 2 | Highly integrated, dynamic, agile interface with all datasets in communication to draw rapid correlations and insights in one platform, improves communication across teams and breaks down silos

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