November 2010
Columns

What’s new in exploration

Snap, crackle, pop

Vol. 231 No. 11
Production
CHRISTOPHER LINER, PROFESSOR, UNIVERSITY OF HOUSTON    

Snap, crackle, pop

In an earlier column about shale gas (May 2010, p. 15), I mentioned microseismic data, but had no room there to develop the subject. Here is our chance.

Recall that conventional seismic is the result of generating waves with an active source, such as vibroseis or explosives, at the earth’s surface. The waves bounce around in the subsurface, and those that return are measured by surface sensors. This is the nature of 3D seismic, a multi-billion-dollar industry with nearly a century of development behind it. This kind of seismic data is processed using migration to create a subsurface image, as discussed in earlier columns.

Microseismic (MS) data is fundamentally different in three ways. First, the seismic source is a break or fracture in the rock, deep beneath the surface. In response to reservoir operations like fluid production, injection or hydraulic fracturing, stresses change and rocks crack, groan and pop like the rigging of an old schooner. Unlike standard controlled-source seismology, in MS each event is a small seismic source with an unknown (x,y,z) location and an unknown source time.

Second, microearthquakes are very weak sources with Richter magnitudes of 0 to −4. To put this in perspective, it would take about 8,000 of those smallest events to match the energy in an ordinary firecracker. Seismic waves from such a source are generally too weak to register at the earth surface due to scattering and absorption by weathered near-surface layers. Consequently, MS data are best recorded by downhole sensors below the weathering zone. This means that, unlike conventional seismic data, MS data acquisition requires the use of monitoring boreholes. Furthermore, with surface seismic data we tell the source when to act and can begin recording data at that time. Since the MS sources can act anytime, we need to listen continuously.

Third, what it means to process MS data and the kind of product created are essentially different from conventional seismic imaging. MS is fundamentally and unavoidably elastic, meaning we must deal with both primary and shear (P and S) waves generated by each MS source. A method of detecting P and S arrivals is needed and must be coordinated among all sensors to ensure that picked events are correctly associated with a common MS event. Assuming all of that is done correctly, we are left with a triangulation problem to locate the MS event location in 3D space. While conventional seismic creates a 3D image of the subsurface, microseismic generates a cloud of subsurface points.

There is more. From a long history of global earthquake science, we know that when rock ruptures, seismic waves are generated with different strengths in various takeoff directions away from the source. In other words, each MS event has not only a time and location, but also a radiation pattern. The radiation pattern is packed with information; it can be inverted to determine an equivalent set of forces that would create the same pattern, and this in turn can be used to determine the nature and orientation of the slippage that caused the MS event. Fractures that open horizontally can be discriminated from vertical ones, north-south trending fractures from those oriented east-west, etc. This is a vast amount of important information.

The heaviest use of MS data to date is frac job monitoring in shale gas plays. Although earlier MS work was done, some of it looking at mapping flow pathways related to conventional hydrocarbon production, shale gas has cranked up the effort by orders of magnitude. Service companies are forming MS divisions, small and nimble new service companies are springing up, and academic research efforts are underway.

So what is this vital information that MS tells us about frac jobs? Certainly we are not interested in the minutiae of a single event. It is the pattern of vast numbers of events that matter. Shale is so tight that virtually no gas is produced from unfractured rock. Without MS technology, it is simply assumed that the frac job has modified the desired volume of reservoir rock. With MS, we can plot event locations and associate them with stages of the frac job to confirm the affected rock volume. This feedback, well after well, allows an operator to change practices to optimize frac coverage and thus maximize gas yield. The best operators and service companies are on a steep learning curve that is increasing estimated ultimate recoveries dramatically in just the last two to three years.

As good as this is, we are still left with an uneasy feeling, like the old joke about a man looking for his keys under a street lamp because that’s where the light is best. Frac job monitoring only happens where the well is drilled. But we also want to know if we are drilling in the best location, in the mythical Sweet Spot. Here, too, MS has the potential to help.

Over the last two decades, the seismic industry has made tremendous advances in data quality through acquisition and processing research. In parallel, the entire field of 3D seismic attributes has developed until they number in the hundreds: coherence, curvature, variance, spice and too many more to name. Many of these afford extraordinary views of the subsurface, including long linear features that appear to be fracture fairways and trends. But as anyone who interprets satellite imagery will tell you, lineaments (as they call them) are darn near everywhere, and you only know what they mean by ground checking.

Where can we find ground truth about the many conflicting fracture indicators we get from 3D seismic? Consider a 3D seismic volume in which a horizontal shale well is drilled. The well is fractured and MS data acquired. Frac jobs tend to open up the rock first along preexisting zones of weakness like natural fractures. By integrating MS data into the seismic volume, we can explore the universe of 3D attributes looking for a connection. Is there an attribute, or combination of attributes, that can highlight the natural fracture trends indicated by the frac job? If so, we have something new in the world: a 3D seismic fracture mapping tool validated by microseismic data.

The game’s afoot.  wo-box_blue.gif
 


C. L. Liner, a professor at the University of Houston, researches petroleum seismology and CO2 sequestration. He is the former Editor of Geophysics, author of the textbook Elements of 3D Seismology, and a member of SEG, AAPG, AGU and the European Academy of Sciences. Read his blog at http://seismosblog.blogspot.com.


Comments? Write: cliner@uh.edu

 

 

 

 

 

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