Researchers visualize subsurface resources with algorithms
Researching improves the understanding and control of subsurface earth resources, which could reduce cost and the carbon footprint.
Enhancing machine learning capabilities in oil and gas production
Enhanced machine-learning systems developed by Texas A&M researchers can quickly compress data so they can render how fluid movements change during production processes.
Improving clean produced water for hydraulic fracturing processes
Researchers at Texas A&M University are investigating cost-effective methods to produce clean produced water so it can be further treated and used in hydraulic fracturing processes.
Merging mapping methods to find invisible shale cracks
A student researcher at Texas A&M is using the combination of electrical currents, called electromagnetics, and data from tightly-focused microseismic measurements to accurately render existing natural fracture networks in shale rock.
Overcoming small organic barriers could reap larger oil recoveries in shale reservoirs
Texas A&M University researchers have found the presence of kerogen plays a vital role in how easily carbon dioxide can travel through shale reservoirs, which could help oil and gas companies reap larger oil recoveries.