[Download the Higher Resolution Subsurface Imaging white paper.]

It is hard to read road signs if you have poor eyesight, which is why driver’s licenses are issued with restrictions requiring that corrective lenses must be worn. Likewise, it is hard to find and exploit subsurface resources if you can’t clearly see your targets or monitor the movement of fluids in the reservoir.

Engineers now have powerful tools to precisely model subsurface reservoir production behavior, but a precise answer is still wrong if it is derived from an inaccurate subsurface description. Geoscientists make maps and rock property models of the subsurface by interpreting images that are produced from remote sensing data. Analogs from modern depositional environments and outcrop exposures guide subsurface data interpretation to predict ahead of the bit, then postdrill geostatistics are used to fill in stratigraphic details between wellbore control points. Selection of the right depositional model, facies distribution, and geostatistical analog depends on having the sharpest, most detailed and accurate image of the subsurface possible—the Grand Challenge of Higher Resolution Subsurface Imaging.

Over the past century, the industry has relentlessly sought ways to improve subsurface imaging of hydrocarbons. Canadian inventor Reginald Fessenden first patented the use of the seismic method to infer geology in 1917. A decade later, Schlumberger lowered an electric tool down a borehole in France to record the first well log. Today, advances in seismic and gravity data acquisition, electromagnetics, signal processing and modeling powered by high-performance computing, and the nanotechnology revolution are at the forefront of improved
reservoir imaging.

In this paper, we will examine the challenges of getting higher resolution subsurface images of hydrocarbons and touch on emerging research trends and technologies aimed at delivering a more accurate reservoir picture.