Reservoir characterization

Search for Elusive Sweet Spots Is Changing Reservoir Evaluation

The pursuit of sweet spots in unconventional oil and gas plays is driving the creation of an emerging set of data-driven systems to measure, map, and predict how wells will perform in unconventional reservoirs.

This map created by Pioneer Natural Resources shows the relationship between pore pressure and standalone well performance in the Midland Basin of west Texas. It was created using data from approximately 2,000 vertical well completions. Well locations are colored and sized based on the estimated ultimate recovery of oil.
Image courtesy of Donny Loughry, senior geologist, Pioneer Natural Resources. Used with permission.

The pursuit of sweet spots in unconventional oil and gas plays is driving the creation of an emerging set of data-driven systems to measure, map, and predict how wells will perform in unconventional reservoirs.

Over 3 days at the recent Unconventional Resources Technology Conference in San Antonio, Texas, speakers outlined techniques used to create detailed, large-scale digital maps and models to navigate enormous formations where abrupt, unpredictable change is the norm. The conference was organized by SPE, the American Association of Petroleum Geologists, and the Society of Exploration Geophysicists.

The developing systems mesh together different sorts of information and experts with a dizzying array of skill sets. One paper described how to complete wells better using: “Advanced Petrophysical, Geological, Geophysical and Geomechanical Characterization” for more productive fracturing.

At the conference, there were presentations about unconventional field studies from BP, Callon Petroleum, ConocoPhillips, Devon Energy, Pioneer Natural Resources, and Talisman Energy, to name only companies that had done work in Texas.

The plunge in oil and gas prices that is driving layoffs and deep budget cuts by operators and service companies is pressuring unconventional oil producers to seek affordable ways to increase production and eliminate wasteful spending on unproductive drilling and fracturing.

“We are in an ever-changing, low-cost environment. We are looking for the most optimal, cost-effective methods,” said Nancy Zakhour, a completion engineer at Callon Petroleum, who worked for Schlumberger during the project. The comment was made during a presentation (SPE 178575) about a project done by Callon and Schlumberger using microseismic, pressure measurements while fracturing, core analysis, and mineral testing to confirm and add detail to 3D seismic testing to create data-rich, digital rock property maps.

That presentation hit on a common theme at the conference: finding ways to navigate reservoirs that are highly heterogeneous, which means conditions can change as abruptly and unexpectedly as the production of the wells drilled.

Pioneer has been combining data and 3D seismic to provide its exploration and production (E&P) team with better views of the spaces between its wells in unconventional formations. Seismic surveys cover a wide area at a relatively low price, but operators want greater detail and physical evidence of rock properties. “The ultimate goal is saving time and money using seismic integrated” with other sources, said Beau Tinnin, a geologic coordinator in the South Texas Asset Team at Pioneer.

Callon Petroleum created a rock property map using seismic data (P-Impedance) ranking rock from the most easily fractured—brittle—to the least—ductile. The microseismic data from fracturing a lateral in the Wolfcamp formation shows the most events in the five stages with above-average brittleness, where much of the activity was contained in the more ductile area. Graphic courtesy of Callon Petroleum.


For one, the work sought out spots where the rock is brittle and easily broken when hydraulic force is applied, and spots with high clay content to avoid, where the rock is ductile and fracturing may prove futile.

“You need to know what you are fracking to know if your wells will do any good,” Zakhour said. Answering that question will require Callon to evaluate enormous numbers of possible well landing zones within the Wolfcamp, a formation found in the Permian Basin in west Texas, which can be 2,500 ft thick.

“What Callon is talking about other people are doing,” said Robert Hull, geoscience adviser for Pioneer Natural Resources, who cochaired the session. Speakers at the conference offered a quick overview of methods too detailed to explain in a 20-minute talk. Those presentations also avoided proprietary information, such as sweet spot locations.

While papers covered work going back as many as 5 years, this is a developing area of expertise. There is no generally accepted method for data-­driven reservoir analysis. Companies with similar goals use different methods, and many operators are still relying on trial and error, often based on what seemed to work for another company working nearby.

Pioneer’s multiple presentations outlined its ways to acquire comparable microseismic surveys, predict pore pressure over a large area, derive the most value out of the fewest mineral measurements, and combine that data with 3D seismic surveys to create maps and models used for critical decisions, such as how to space wells most efficiently.

The work highlights the shortcoming of approaches developed to find and produce hydrocarbons in conventional formations where hydrocarbons are trapped in porous, permeable reservoirs. In a shale, the “reservoir” is a microscopic network of pores connected by throats so small that they can only be seen with high-powered microscopes. Conventional analysis methods were developed for reservoirs that have “nothing to do with shale,” said Shahab Mohaghegh, a petroleum engineering professor at West Virginia University.

“The formulations that are currently used to model fluid flow (and therefore production) in shale do not really represent what is happening and, therefore, scientists and engineers cannot fully trust the results generated by these models,” he said in a paper (SPE 178504) presented at the conference.

Mohaghegh described the goal of data-driven methods as trying to “extract maximum knowledge” from measurements, which typically require the use of advanced analysis methods such as artificial intelligence.

Engineers need alternatives to deterministic models based on measurable cause-and-effect relationships, because the required information is lacking. For example, fracturing results depend on interactions between natural fractures and the impact of hydraulic force, none of which can be directly observed or measured, making it nearly impossible to determine how natural and engineered forces contribute to production.

The presentations represent years of work that looked at reservoirs in ways that blur the definition of what engineers and geoscientists are expected to know and do.

“In unconventional shale, a reservoir’s fracture permeability (both natural and induced) largely dictates well performance. This suggests that the modern geoscientists’ “tool kit” requires innovative techniques, which begin to bridge the gap between various geoscience and engineering disciplines,” wrote Paolo Grossi, a geologist at Talisman Energy USA, a part of Repsol, in a paper on methods used to measure the good and bad effects of fracturing within wells.

Unconventional Thinking

The large number of wells and fracture stages producing little or nothing of value is a strong argument for change. While publicly traded companies do not report results on a well-by-well basis, there is anecdotal evidence that underperforming wells are a financial drag.

A rule of thumb offered by George King, distinguished engineering advisor for Apache Corp., is that “one-third of the wells are not economic, one-third are marginally economic, and one-third carry the economics for the whole project.” The observation made during a panel session about sweet spot identification is not a new one for King, who often speaks and teaches about shale.

When asked if this static breakdown means there has been no progress, King said it does show that the technology is advancing because profitably drilling and completing a well has gotten so much harder at these low prices.

The phase, “key to production,” was a favorite with many speakers. Some offered enough keys to crowd a ring. With limited time and money, operators are working to winnow down the number of key markers for sweet spot identification to an essential few.

Baker Hughes created a list of key properties associated with the most productive unconventional wells, starting with 18 and reducing it to 6, said Usman Ahmed, vice president and chief reservoir engineer at Baker Hughes Reservoir Technology.

Baker Hughes lists six indicators of reservoir quality:

  • Total organic content: the source of oil and gas if present
  • Reservoir pressure: the energy needed for production
  • Vitrinite reflectance: a thermal maturity measure to determine if oil or gas production is likely
  • Brittleness: brittle rock shatters when hydraulically fractured
  • Permeability/natural fractures: successful hydraulic fracturing builds on natural fracture networks
  • Porosity: storage space available for hydrocarbons

Source: Usman Ahmed, Baker Hughes.

A Pioneer study (SPE 178592) seeking proxies for critical rock properties found that it could use just two elements, molybdenum and aluminum, to identify hydrocarbon-rich rock that is easily fractured. Molybdenum levels were a proxy for the total organic content, which is a proxy used to locate oil-rich rock. Aluminum oxide levels were used as a proxy for a rock’s clay content, which is used to determine how well the rock will fracture, Tinnin said.

Those are all prerequisites for production. But when asked about what is the most important when seeking sweet spots, Gervasio Barzola, vice president of subsurface and development in the Southern Wolfcamp Asset Team at Pioneer, repeatedly pointed out that pore pressure is the critical variable. “Where there is no energy in the reservoir, you are not going to make a great completion,” he said.

Reservoir pressure is on the Baker Hughes list and it has long been important when evaluating prospects. But predicting that vital number at a specific location before a well is drilled presents a challenge in these highly variable formations.

A Pioneer paper (SPE 178649), which described how the company created a map of pressure levels for its acreage in the Midland Basin in west Texas, observed: “Many operators acquire direct measurements of the formations using costly and/or time-consuming methods, but are most often left only with a general understanding of the pressure regime in and around their respective acreage.”

A description of the work done by Pioneer to create a pore pressure database covering its large acreage position may help explain why others have settled for less. The huge study drew on the company’s trove of historical pressure measurements.

The company’s pressure database includes more than 8,600 instantaneous shut-in pressure measures from nearly 2,000 vertical wells, diagnostic fracture injection tests in specific zones, bottomhole pressure data, pressure readings from electric submersible pump data, and the mud weights used to control the reservoir while drilling 185 horizontal wells.

The investment was large, as is Pioneer’s 785,000-acre holding in the Midland Basin. “The pore pressure mapping effort, while labor-intensive and technically challenging, allowed for the integration of a vast amount of geologic and engineering data,” said Donny Loughry, a geologist in Pioneers’ Southern Wolfcamp Asset Team. The payoff has been to “dramatically increase our understanding of how to exploit the reservoir from appraisal through full-field development.”

The maps, offering localized predictions of the pressures likely at specific locations and depths, have been use to decide on  well spacing, drilling locations, and completion plans. But, the paper pointed out that “most importantly, though, this model helps us understand well performance.”

Detecting Tiny Details

An indication of the need for better sweet spot identification is the studies showing that 30% to 50% of all fracture stages fail to produce, Ahmed said. It is widely known that a lot of stages were a waste of money. The hard part is knowing which stages will not work before spending the money.

A likely cause of failed fractures is a lack of pathways connecting the oil in the rock’s pores and the wellbore. In rock where the matrix is nearly impermeable, reservoir access requires natural fractures reached by using hydraulic fracturing.

“I do not think there is anything out there if there is not a natural fracture network,” said King. The common practice of fracturing stages at regular intervals in a well without evaluating if those spots will be productive is one reason that two-thirds of all wells are marginal to bad investments, he said.

Applying that advice requires making judgments on the location of features too small to be directly detected. The solutions offered all pointed to indirect ways of detecting where openings are likely, starting with gas influxes during drilling. Small ones often occur when the mud pumps are turned off for pipe connections. King said if the origin of the gas shows is accurately identified, they can point to where natural fractures are found in the reservoir. Where there are no gas shows, there may be no reason to pay to fracture that spot.

“I have used it 100 times and it works reasonably well,” he said. This requires close attention to when the gas separator is removing gas from the mud to predict the location in the reservoir producing the gas. When asked for data supporting the effectiveness of the approach, King said the method had not been rigorously tested. “It is not a highly scientific process, but it is a really cheap process,” he said.

A Talisman study (SPE 178508) looked at how natural fractures in a complex area within the Eagle Ford formation led to significant production variations with sections of four wells drilled on a pad in the south Texas play, Grossi said. The variations caused by the geologic history and stress variations created features that could explain the best and worst production results.

A Talisman analysis divided sections in four wells on a drilling pad into three classes. The illustration, which is not of an actual well, showed the characteristics associated with those groups. The best results were in Class 2, center, where the fractures (red) stayed within the productive zone. The worst results were in Class 3, right, where fractures left the zone. Graphic courtesy of Talisman Energy.


Gas influxes were used as an indicator of whether those factors created natural fractures that added to, or reduced, productivity in an area. Gas from kicks that occurred while doing underbalanced drilling, in which the low mud weight used allows some influxes, indicated the presence of potentially productive fractures.

The locations of influxes were seen as “an initial indicator of potential natural fracture systems in low permeability reservoirs,” according to the paper. Talisman also recorded the level of liquid content in the gas. A shift in that measure may suggest a change in the fracture network.

The salinity level of the flowback water may also be an indicator of the extent of natural fractures. The highest salinity levels were thought to indicate that fracturing fluids had entered deep into natural fracture systems. When used with other observations, “flowback water testing can be used as an early indicator of long-term well productivity,” the paper said.

Ultimately, the study of a well pad within the Eagle Ford divided the area covered by those wells into three groups.

The best performing were found in Class 2, which had significant fractures confined to the production zone. The worst results were in Class 3, which Grossi described as “bad news.” Hydraulic fracturing was unproductive in Class 3 sections, likely because the natural fractures extended out of the Eagle Ford to adjoining layers—up into the Austin Chalk and down to the Buda—which could have dissipated the force of hydraulic fracturing with the production zone.

Free Data

In this brutal economic environment, exploration teams are seeking the lowest-cost data-gathering methods. For Pioneer, that has included acquiring data by trading with the owners of nearby wells, and extracting more information from its current routines.

At the end of a session (SPE 178592) on a Pioneer project to gather geochemical data from 180 wells, the presenter thanked the field geology team, especially the mud loggers collecting cuttings off the shale shaker. The project relied on them to regularly collect cuttings to evenly sample the wellbore, and test the makeup of those rocks using a handheld X-ray fluorescence (XRF) device.

Adding the XRF geochemical data to 3D seismic data that was processed to show rock properties—Poisson’s ratio and Young’s modulus—created a more detailed and reliable decision-making tool.

There are also important rock measures that are not practically attainable. For example, it is known that fracturing in unconventional reservoirs is significantly affected by the fact that the rock is inherently anisotropic, with physical properties such as strength that vary depending on the direction measured. This difference has a significant effect on the mechanical properties of the rock and also on measurements of horizontal stress, particularly when one is trying to calculate the stresses from log data, said Norm Warpinski, a technology fellow at Halliburton’s Pinnacle unit.

These directional differences can determine if a fracture is short or long, simple or complex, or whether one develops at all. “If we do not understand these rock and reservoir characteristics, we will not be able to determine how fractures and fracture networks may develop,” Warpinski said.

Logging tools are unable to gather the information needed to characterize anisotropic rocks, he said. Laboratory tests can help answer the questions, but their use is limited by the cost and time required for testing, and challenges associated with gathering a representative sample. Better measures of the interplay between reservoir stress and anisotropy are needed because when developing an unconventional formation “stress conditions are huge,” he said.

For Further Reading

SPE 178504 Formation vs. Completion: Determining the Main Drivers Behind Production From Shale; A Case Study Using Data-Driven Analyticsby Shahab D. Mohaghegh, West Virginia University & Intelligent Solutions.

SPE 178508 Investigating Natural Fracture Effects on Well Productivity: Eagle Ford, La Salle County, Texas by Paolo Grossi, Talisman Energy USA.

SPE 178516 Finding the Key Drivers of Oil Production Through SAS Data Integration and Analysis by Beau Rollins and Matthew Herrin, Devon Energy.

SPE 178575 Integrating 3-D Seismic and Geomechanical Properties With Microseismic Acquisition and Fracturing Parameters to Optimize Completion Practices within the Wolfcamp Shale Play of the Midland Basin by Michael Shoemaker, Callon Petroleum Co.; Nancy Zakhour, Schlumberger; et al.

SPE 178591 An Integrated Approach to Stimulated Reservoir Interpretations of the Permian Wolfcamp Shale by D.R. Collins and G. Monson, Pioneer Natural Resources, et al.

SPE 178592 Multi-Source Data Integration: Eagle Ford Shale Sweet Spot Mapping by Beau Tinnin and Matthew D. McChesney, South Texas Asset Team, Pioneer Natural Resources, et al.

SPE 178649 Using Pad ISIP, DFIT, and ESP Data to Generate a Pore Pressure Model for the Midland Basin by Donny Loughry and David Epps, Pioneer Natural Resources, et al.

SPE 178715 High Fidelity Microseismic Data Acquisition in the Midland Basin Wolfcamp Shale Play West Texas, USA by Robert Hull and Robert Meek, Pioneer Natural Resources, et al.