Innovative thinkers

John Quirein, PhD

As the industry progresses further into unconventional oil and gas production, technology and R&D have become essential tools in their exploitation. 

While, relatively, the same kinds of equipment are used today as have been for decades, the oil and gas industry is pushing the boundaries of technology and thought, combining computational power with raw force to exploit the earth’s resources. The industry’s continual advancements utilize not only experts in petroleum engineering and geophysics, but also modeling theorists and mathematicians, all of whom contribute greatly to oil and gas accessibility.

“In today’s unconventional plays we’ve gone from exploration to extraction. The recipe varies but production is increasing,” said John Quirein, Halliburton Technology Fellow for Wireline and Perforating.

An author of more than 40 technical papers, and recipient of 17 patents, Dr. Quirein started his career in the aerospace industry, as a NASA subcontractor with Lockheed. He worked on the Large Area Crop Inventory Experiment (LACIE) Project, which used satellite imagery data to scan crops. The objective was to predict acreage planting, and predict yield from satellite data. 

“That project introduced me to the field of statistics, and pattern recognition,” Dr. Quirein said. “We interpreted satellite data to delineate the best place and time to plant wheat, using classification theory.” The LACIE experiment used algorithms to recognize patterns, developing more sophisticated pattern recognition. Back then, Dr. Quirein said, computing power was nowhere near today’s capability. “Too many inputs, and the computer slowed down, so my team addressed the question of which of those inputs were the most significant or important. This process is called the feature selection problem.”

Feature selection became the subject of Dr. Quirein’s PhD thesis, which he earned in mathematics from the University of Houston. Dr. Quirein’s team looked at satellite imagery, and extracted texture. The image-based texture features would vary from dark to light, and they developed more advanced pattern recognition algorithms, applying algorithms of neural networks to determine an optimum harvest.

That application of neural networks carried over to the oil and gas industry—in particular, wireline well-log and seismic interpretation, which brought Dr. Quirein to Schlumberger in 1978. “My initial training for NASA was quite applicable (to wireline logging). Borehole image data were transformed into textural features, so we used the same thing in well log data.” 

After 10 years at Schlumberger, Dr. Quirein worked at Mobil Oil for 12 years. He now is in his 15th year at Halliburton.  

“Today, (my work) is all about integration: How to integrate measurements of different scales, and how to bring those scales together. What are those logs seeing? More recently, at Halliburton, we’re focusing on an asset expert interpretation series. Shale and unconventional plays are spread out, and are huge, but the problem is having to figure how best—in a cost-effective manner—to get (the hydrocarbons) out,” Dr. Quirein said.

“The emphasis has changed from an exploration point of view, to one of extraction. We know where (the source rock) is, and with enough historical evidence, we know oil is there, but how can we extract it economically? My work helps operators determine how to construct frac staging, and where to locate the perforations within those stages.” 

Optimal extraction varies from shale to shale, and over time, fewer wells are drilled, but the production is increasing per well. Dr. Quirein ties that success into the microseismic work, predicting where, subject to interpretation, one should, and should not, frac. “We’re using all of this to try and create fracture models.”