Formation Evaluation Logs for Horizontal Wells
Near Real-Time, On-Demand, or After TD
Cost-Effective | Safe | Non-Intrusive
Critical Information for Your Drilling & Completion Program

Who We Are

Formed in 2012, Quantico Energy Solutions is a data analytics company based in Houston, Texas. The company’s focus is on providing the oil and gas industry with data-driven solutions that address major challenges in the development of shale resources worldwide.

Our company employs a leading team of professionals from the oil and gas industry. The team has expertise in machine learning software, open hole logging tool design, geology, geophysics and completion engineering. We develop proprietary software to predict synthetic formation evaluation logs by utilizing only the information commonly gathered during the drilling process.  

Why is this important? We believe that if oil companies have better access to rock mechanics and lithology information in unconventional wells, then drilling and completion programs can deliver significantly higher production and cost savings. In conventional oil and gas projects that run LWD tools, our synthetic logging approach can provide a risk-free contingency and cost saving measure that lowers overall logging costs by millions of dollars. 

Horizontal Formation Evaluation Logs



Quantico’s QLog service provides a suite of synthetic logs including shear, compressional and density. QLog can be run for both horizontal and vertical wells. The benefits to the oil company are: No separate logging run after the well is drilled. No nuclear or acoustic sources in the well. Results as fast as within minutes of drilling your well.


Real-time neutron, density and sonic logs while drilling. Now QDrill can assist with ROP optimization, wellbore stability and well placement decisions in projects where LWD services were previously not economically viable. For projects that run conventional LWD tools, QDrill can serve as a reliable add-on service that increases reliability, reduces NPT and logs every trip.


Using the primary logs from QLog, additional properties including Poisson’s Ratio, Young’s Modulus, Brittleness, Horizontal Stress and Lithology can be derived. The QFrac service provides these additional logs as well as a recommendation for an engineered completion design based on the interpretation of these formation properties by leading experts in the industry.


A typical horizontal well has ~20-40 times more samples in target zone than corresponding vertical well and with large lateral coverage. QRes enables more calibration constraints on seismic inversions, leading to less requirement for non-unique interpretation, or equivalently, a higher inversion resolution.

How Does It Work?
  • Step 1: Drilling data sent to Quantico in real-time or after TD
  • Step 2: Quantico processes input data in proprietary software
  • Step 3: QLog and QFrac sent to oil company
    • Files delivered in .las format
    • Usable in conventional log analysis software

Why Run QLog?


QLog will save you from 50% to 90% compared to logging alternatives including slim-hole logging tools, pulsed neutron (or behind casing) derived logs, and advanced cuttings analysis.


Demonstrated in multiple shale basins, QLog has the leading accuracy and reliability (per dollar spent) of any open hole logging solution in the industry. See FAQ.

No Risk

No nuclear sources enter the well. No chances of sticking or losing a tool. No added personnel on-site. No additional lost-in-hole or HSSE risks.


With no added tools placed in the well, QLog avoids disrupting any rig operations or production equipment.

No Tool Failures

Tough-hole conditions or tools failures? Run a QLog rather than risking another logging run or not obtaining any log at all.


QLog can generate open hole logs in any production well where the original drilling data is available. This means logs can be obtained on wells drilled 5+ years ago.

Quantico’s QFrac service represents a valuable ‘big data’ solution to the stimulation process. By using the drilling data you already have, this service makes it much easier and cost-effective to initiate fractures and equalize proppant distribution in multi-cluster stages.

StrataGen, Frac Consultant


1.How does QLog compare to conventional horizontal logging tools?
Consistent Accuracy

QLog simulations have been demonstrated in several blind tests to exhibit accuracy consistent with conventional horizontal logging tools. In order to perform the benchmarking, three wells were identified where log-off data was available from two conventional logging tools being run in the same wells. The mean squared error (MSE) was calculated between the two sets of conventional logs (shown in red in the graphic below). The MSE was also calculated between QLog and a set of logs from a conventional tool (shown in blue in the graphic below). As demonstrated in one blind test, the accuracy QLog was in-line with the accuracy of conventional logging tools. In other words, the accuracy of QLog is similar to what would be expected if the same conventional logging tool were to perform a re-log.

Reliable Sonic

After conventional logging tools have been run, proper waveform processing is required in order to generate a high quality sonic log. Sometimes, this processing may be performed manually by an engineer or it may be automated with software used in the field. This added step creates an opportunity for erroneous waveform selection in certain intervals of the well. Potential poor results include Compressional locked on Shear arrival, Shear locked on Stoneley arrival, or unrealistic wavy slowness. Reprocessing of the waveforms can be expensive and difficult of the original logging data was not retained. QLog avoids this process altogether in simulating its sonic logs.

Quality Measurement

With conventional logging tools, poor sensor contact, centralization and issues caused by washouts lead to erroneous measurements. Relative to vertical wells, the difficulties in horizontal wells of proper sensor pad contact and centralization are heightened. However, the input parameters utilized by QES’ machine learning software are not impacted by such impediments. QLog results are substantially less prone to these types of measurement errors sometimes witnessed in logs from conventional tools.

2.How does QLog compare to logs derived from Gamma only?
Drilling dynamics significantly increases reliability

The accessibility of Gamma logs has in part made them a widely used approximation when examining the rock mechanics along horizontal wells. However, it is also widely understood that Gamma does not reliably reveal changes in sonic and density properties. The histogram below compares the results of over 70 Permian simulations with A) Gamma and Drilling Dynamics data as the input parameters used to transpose measured horizontal logs from Well X to simulated horizontal logs in Well Y, versus B) doing the same using Gamma as the only input parameter. The models that included the Drilling Dynamics data exhibited significantly more reliable predictions – specifically, how often they were more accurate, and in such instances, the size of the accuracy gains.

3.How does one know whether engineering completions will help?

The key question for many operators is will engineering completions enhance production and/or lower cost? And will the gains be large enough to matter?

There are increasing data points in industry literature to suggest that changing the placement of stages and perforation clusters to coincide with rock mechanics and lithology can indeed help. However, there are also instances where the results from testing engineered completions on a handful of well did not lead to statistically significant uplift.

QES believes that every reservoir is unique. Thus, the results of engineering completions will vary by reservoir. The only way to know the answer on your reservoir is to perform tests with sufficient sample size to generate statistically significant results. And in today’s budget constrained environment, to do so in a manner that does not increase costs or jeopardize production. 

Production across shale basins in highly variable. The Utica data set shown below is as follows:

(a) Sample set of 641 Utica wells placed on production during 2014
(b) 90 day average daily production of 714 bpd
(c) +/- 34% of wells (1 standard deviation) high as 1,306 bpd, low as 121 bpd

The conclusions from this data set suggest:

(1) Large range in 90-day IP indicates high variability in geology; and drilling, stimulation and completion methods.

(2) Given such high variability, a large amount of well data is needed to identify methods to improve production. For example, if one only had 90-day IP data from 10 wells, then estimating with a 95% confidence interval what the expected production would be would lead to a range from 347 bpd to 1,081 bpd in the Utica. Conversely, if average 90-day IP were 714 bpd (based on this dataset), and one desires to predict with 95% confidence interval the expected range of production within plus/minus 116 bpd (20% of the average), then he/she would need to gather production data from 100 wells.

Assuming that the number of stages and perf clusters in an engineered well are designed to be the same as a geometrically completed well, then the primary cost of the study normally arises from the added logging costs and some incremental amount of engineering and interpretation time. With QLog, an operator could obtain logs on 50 wells for the same cost as logging 5 wells with conventional tools.

The high volume of wells being drilled in shale basins across North America means that even small improvements in field wide IP and/or capex will lead to significant NPV gains. If the logging costs can be removed as a constraint to testing engineering completions, then operators can finally determine the potential impact on their reservoir.

Logging While Drilling

Real-time or on-demand synthetic logging provides critical information for projects where conventional LWD services were previously not economically viable. For projects that run LWD tools, a software-based approach can serve as a reliable add-on service that increases reliability, reduces NPT and logs every trip..

Engineered Completions

Take the horizontal logging cost and risk factors out of your decision to engineer completions. Or have the liberty to conduct a multi-well program to test various placement and design criteria with minimal impact on the AFE.


QLog is the only solution that allows you to obtain open hole logs on wells already put on production. The ability to review formation properties on wells drilled years ago is critical to selecting candidate wells to re-fracture. Now utilize rock mechanics and lithology to selectively target promising intervals.

Reservoir Mapping

A typical horizontal well has approximately 20-40 times more samples in the target zone than a corresponding vertical well and with large lateral coverage. Utilize the horizontal sonic logs to better calibrate seismic between pilot wells, map geomechanics across a trend, and better calibrate microseismic velocity models.

Case Studies


September 28, 2016 – QES Co-Authors Paper Presented at
SPE ATCE: Big Data Yields Completion Optimization


August 1, 2015 – QES Featured in 
Journal of Petroleum Technology


May 4, 2015 – QES Announces Investment from
Shell Technology Ventures and Statoil Technology Invest


Contact Us

If you would like to find out more,
please get in touch with us.

Quantico Energy Solutions, Inc.
5800 Ranchester Drive, Suite 200
Houston, TX 77036



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