The competitive advantage in drilling has shifted toward how quickly information is transferred from the subsurface to the engineer. Chevron’s latest technology shows that when you’re developing oil and gas, the decisions are expensive — millions of dollars — and they’re being made with a limited view.
What is the issue with central analysis?
The modern unconventional basins (Permian) include tens of thousands of wells. Each well is uniquely influenced by its own geology, its history of decline, and engineering decisions made to optimize its performance. Historically, engineers used generalizations and retrospective analysis to evaluate drilling locations. These methods were generally successful at the basin-wide level; however, they often smoothed out local differences that would determine whether a well performs better than expected or does not meet expectations.
Chevron recognized that there is a gap forming in the speed at which subsurface data is generated and analyzed versus the point at which those analyses affect drilling and completion decisions. The amount of subsurface data has grown exponentially since the advent of horizontal wells, but humans cannot analyze that much data at a rate to affect drilling and completion decisions in real time.
That created a need for a different type of computer architecture — one that moves the analytical work away from centralized teams and closer to where actual drilling decisions take place.
Chevron is moving intelligence to the edge
Chevron developed APOLO — its proprietary Automated Production Outlook and Location Optimization platform. While it has been characterized in public forums as an artificial intelligence application, APOLO’s defining feature is that it provides the ability to do analytical work closer to operations rather than having all insights routed through centralized teams. Using millions of data points derived from shale and tight rock formations, APOLO creates standardized and explainable production estimates for engineers to utilize immediately.
APOLO uses dynamic forecasting — analyzing relationships between thousands of wells to identify how individual parameters (spacing, proppant volume, fluids) will affect performance within specific geological zones. This provides an opportunity to transform the complexities of the subsurface into actionable direction for operators. APOLO reduces dependency upon assumptions about how wells perform, which are typically made distant from the actual drill site.
Chevron’s engineers find that the difference using APOLO is more practical than academic. Rather than waiting until drilling has occurred to revisit their modeling assumptions, teams are able to make adjustments to their designs using near-real-time data and thus minimize the uncertainty prior to deploying capital.
The real-time data influences drilling decisions
The importance of real-time data-based analytic applications is most evident when examining decisions at the margin. Small changes in either well placement or completion design can significantly affect production outcomes — particularly in declining basins. APOLO allows engineers to run simulations utilizing different design options for specific areas and learn continually as new wells begin producing.
Drilling becomes adaptive — no longer strictly sequential
Chevron has reported that this method of operation improves forecasting accuracy while maintaining transparency. Engineers can observe why recommendations are provided, not simply receive the result. As APOLO continues to evolve through results, it will become increasingly accurate due to an ever-expanding database. APOLO converts drilling into an iterative process. Decisions that previously required extensive review periods can be supported by analytics delivered at the speed of operations.
From drilling tool to asset portfolio optimizer
Chevron views APOLO as something greater than a predictive system. Through standardization of analysis and acceleration of insight across its assets, APOLO aids in optimizing capital expenditures at the asset portfolio level.
APOLO also helps teams focus on potential locations and designs that are most likely to provide optimal performance/cost alignment. Chevron has stated that it intends to expand APOLO’s capabilities beyond both the Permian and DJ Basins to its remaining global shale/tight resource plays. Edge analytics is becoming a critical component of Chevron’s overall development strategy.
