Geoscience-Based Artificial Intelligence For The Subsurface


Loren Ipsum


Loren Ipsum


Loren Ipsum


Loren Ipsum

Optimized Completions

Take the horizontal logging cost and risk factors out of your decision to optimize stage and perforation cluster placement. For the same number of stages, studies have shown that equalizing stress across stages and clusters yields higher production and smoother frac jobs relative to geometric completions.


Loren Ipsum

QDrill generates real-time unconfined compressive strength (RT-UCS) by processing the data already collected during the drilling process. By comparing trends in RT-UCS and mechanical specific energy (MSE), the software is able to distinguish between changes in formation properties versus energy misapplication leading to drilling dysfunction. Now the driller can maintain or return to the efficient drilling window.

Additionally, QDrill recommends the optimal drilling parameters and provides updated formation tops – all in real-time. The formation properties can be delivered at the bit or ahead of the bit to give drilling engineers the necessary lead time to make proper decisions.

QLog provides a suite of synthetic logs including shear, compressional, density and neutron. QLog can be run for vertical, deviated or horizontal wells. Qualification tests with supermajors has shown QLog to provide the same accuracy as LWD tools in both deepwater and land wells. Additional benefits to the oil company include no nuclear or acoustic sources in the well; and savings up to 80% of conventional logging costs.

Now the rest of the quad combo can be obtained by only running Gamma and Resistivity. QLog is an ideal solution to log challenging zones due to drilling hazards, slim hole or highly deviated sections. If an LWD tool malfunctions or loses circulation, QDrill can be turned on to drill ahead.

QRes is able to quickly and inexpensively generate near-log scale resolution earth models. The AI-based process is able to tie seismic to a variety of inputs such as well logs, and then uses the seismic data to map virtually any property across the entire volume (eg, Gamma, Resistivity, Density, YM, PR, etc). Laborious, expensive inversions and interpretations can be eliminated with turnaround time decreasing from months (traditional inversions) to weeks. Inverted volumes can also be utilized for downscaling.

Quantico expands the application of artificial intelligence to production modeling (QResXAI), where public well data from state regulators is used to predict production and inform decisions around well placement and completion design. QResXAI’s advanced methodologies include deep integration between earth models, geophysics and explainable AI so predictions are more accurate and easier to audit.

Using the primary logs from QLog, additional properties including Poisson’s Ratio, Young’s Modulus, Brittleness, and Minimum Horizontal Stress can be derived. These properties can be used to derive vertical and horizontal stress profiles, model frac treatments and optimize the placement of perforation clusters and plugs to correspond to changes in rock characteristics.

Employed in over one hundred US Land wells, the optimized placement has shown increased production, smoother frac jobs, and lower overall completion costs.





Your text

Your text




Real Time UCS


Tops While Drilling




Post-Drill Logs

Loging While Drilling





Hi-Res Earth Model

Shale Production Model

Well Placement




Horizontal Logs


Completion Placement

Case Studies