Finding production trends, parameters

Eagle Ford Data Base Provides a Sweet Spot

Current oil and gas wells in the Eagle Ford: Production is mapped and highlighted as bubbles for selected wells; total well depths shown and contoured as depth surface.
Current oil and gas wells in the Eagle Ford: Production is mapped and highlighted as bubbles for selected wells; total well depths shown and contoured as depth surface.

Unconventional shale plays are nothing if not complex.

The booming Cretaceous Eagle Ford play in south Texas is a prime example.

Covering 11,000 square miles, it’s a depth-driven resource with oil produced as deep as 8,000 feet in the northwest, continuing through condensate and natural gas liquids and on to dry gas as deep as 12,000 feet to the southeast.

Production tallies more than 1 MMboe/d from 3,500 producing wells.

The spoiler for the operators?

A data base like this – including total depth and other production data – has become a valuable predictive tool in the Eagle Ford play.
A data base like this – including total depth and other production data – has become a valuable predictive tool in the Eagle Ford play.

Variable well production makes it difficult for these folks to high-grade sweet spots and optimize well spacing and completions.

Even so, some operators are using the factory approach to field development, laying out a systematic horizontal well pattern across prospective acreage.

Murray Roth
Murray Roth

In addition to variable production volumes, there’s a high degree of variability in well length and orientation, number of fracture stages, and hydraulic fracturing volumes and rates, according to AAPG member Murray Roth, president of Transform Software Services in Highlands Ranch, Colo.

Roth should know.

He and his team created a regional data base of more than 3,500 producing Eagle Ford wells with reported drilling, completions and production engineering data, merged with available geologic top, geochemistry and other relevant data.

They then used predictive analytic techniques to correlate geologic and drilling/completion engineering data with individual well performance to highlight production trends and optimal engineering parameters.

Isolation Play

Once Roth and his team had contoured the maps, depth and thickness could be determined.

“Depth matters,” Roth said, “because you have more pressure the deeper it is, and it’s more likely to be natural gas.

“Now you also have an economic dilemma, and you have to move updip to find the balancing act with your geochemistry to know where the sweet spots are,” he noted. “You can make a depth map, a thickness map and put production on top of that, but a picture doesn’t pop out.

“There’s something else, and clearly it’s the variability in the engineering,” Roth said. “Even after 3,500 wells, it’s difficult to map geologic sweet spots because the wells were drilled and completed in a different way.

“You can’t cross-plot this,” he stated. “You have to let the engineering and the geology speak for themselves in an integrated model and see what emerges from that.”

He explained that this entails making a model and taking the engineering variability out of the model. By mathematically correcting for that variability, you acquire not just a geologic map but a map where production is scaled by this variability.

“I’m taking out the fact that I’m looking at a well, and it’s a long well, and across the county is a short well, and the fact they have three times difference in production won’t help me to understand the geology unless I remove that contamination from my geologic data,” Roth said.

“The technique is about trying to isolate or normalize out the engineering and the geologic effects,” he emphasized.

Otherwise, deceit takes center stage.

Imagine if you created a production map using real production values. There would be a rush to run out and buy acreage in a supposed sweet spot. Then comes the realization that the geology actually is pretty crummy, and people had overcompensated by drilling really long wells.

“You’re being deceived by production because this is not a comparison of apples to apples,” Roth noted.

Getting a Clear(er) Picture

Horizontal length would be the principle parameter to compensate for if the permeability in the Eagle Ford was normal, e.g. darcy, millidarcy versus nanodarcy.

“The additional nuance and complexity of normalization is completions in addition to the drilling,” Roth said. “The complexity in these unconventional plays because of micro-permeability means the geology by itself is not a good factor on sweet spots if you’re looking at production as a metric.”

Think of it this way: Two wells are drilled with 10,000-foot laterals and one produces maybe five times as much oil, but it underwent 30 fracture stages vs. none for the other.

The resulting picture does not define the geology.

A map was created over the course of the workflow during the transform project to indicate what the rocks likely would produce if every well was drilled and completed the same way.

To get a clear picture of what’s going on in the subsurface, you must remove the drilling and completion effects.

“Using a non-linear or multi-variate technique, based upon transforming variables into linear predictors of production, has proven to be a robust and reliable approach for assimilating and understanding the constraints for unconventional well production,” Roth said.

He added they used publicly available engineering data and seismic data provided by Global Geophysical to construct the integrated production prediction model for the Eagle Ford.

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Emphasis: Seismic