Be sure to grab your April issue of First Break, and turn to this month’s special topic: EM & Potential Methods, where NEOS discusses the results from resistivity imaging using ZTEM and MT data in the geophysical study of a ~2900 km2 region of the northern Raton Basin in southern Colorado.
Because of the land access and permitting issues, as well as the large amount of terrain needing to be traversed during the geophysical survey, we decided to incorporate a dense airborne ZTEM survey along with the sparse MT stations.
On the Lebanon neoBASIN regional reconnaissance project, we acquired EM resistivity data from roughly 45 ground-based magnetotelluric (MT) stations that were deployed throughout the survey area. Challenging topography and dynamic geo-political conditions on the ground didn’t always let us deploy the stations where we wanted to, but we did get some interesting results nonetheless.
The MT method relies on three primary sources of electromagnetic (EM) energy, all with different frequency ranges and, therefore, depths of penetration. High-frequency signals originate from lightning, in particular ongoing equatorial lightning strikes; intermediate frequency signals come from ionospheric resonances; and low frequency signals are generated by variations in the solar wind.
Driven by advances in sensors, DP and modeling methods, can computing power, MT has become one of the most important tools in deep Earth imaging with a capability to image to subsurface depths of 10,000 meters or more.
For hydrocarbon exploration, MT is mainly used as a complement to seismic imaging. This is especially true for scenarios that can be problematic for seismic, such as sub-basalt and sub-salt plays. In addition, while seismic is able to image subsurface structure, it cannot detect changes in resistivity associated with hydrocarbons and hydrocarbon-bearing formations.
By measuring both electric and magnetic responses simultaneously and processing the data using statistically rigorous mathematics, MT allows resistivity variations to be mapped with depth in the subsurface. Under the right geologic conditions, MT can differentiate between structures bearing hydrocarbons and those that do not.
In the image above, we analyzed the MT data in several different ways, initially in an unconstrained fashion and then in a constrained inversion where we also considered the measurements from, and structrual models being generated using, airborne-acquired gravity and magnetic data.
The multi-measurement integration and interpretation yielded very good results. In the 2-D constrained EM resistivity section shown, you’ll note several interesting features:
First, the fairly clean resistivity delineations among the key stratigraphic horizons;
Second, the insight EM resistivity information can bring to fault mapping, including the displacement along faults;
Lastly, the interesting intra-horizon resistivity increase as one moves up-section within the Cretaceous.
The scale here is logarithmic, so this is roughly a 10x increase in resistivity taking place within a 500-800 meter thick interval. Equally curious is that it’s taking place along and adjacent to a deeply penetrating fault. Simply an aberration? Noise in the data? A change in lithology? Or a change in fluid type at the highs abutting the fault?
Out this week, First Break’s Annual EAGE Conference Issue, “Experience the Energy”. Get your copy today and skip straight to the “Special Topics” section for the piece on NEOS’ approach to interpreting airborne-acquired EM data much deeper below the surface.
Novel approaches to acquire, process and interpret airborne-acquired, passive-source electromagnetic datasets are now being tested in the field and are showing promise in their potential for delivering new insights…
For millions of years, Appalachian gas has migrated toward the surface along naturally occurring faults. Frequently, it gets trapped in shallow structures difficult to see on seismic images. Abandoned and undocumented wellbores, some a century old, compound the problem. Drilling into a shallow gas pocket en route to the Marcellus or Utica Shale can throw a wrench in operations, forcing a producer to set a string of casing and adding up to $250,000 per well in unexpected cost. Fracing near an orphaned wellbore or unknown fault is every operator’s worst nightmare.
Responsible operators want to know the challenges they face ”ahead of the bit” so they can avoid geo-hazards and design their drilling and hydraulic fracturing programs with utmost regard for the environment. To address these challenges, NEOS GeoSolutions has introduced Eco-Assurance™, a program based on its proprietary Multi-measurement Interpretation (MMI) methodology. A combination of airborne magnetic, hyperspectral and electromagnetic (EM) measurements helps to locate orphaned wellbores, reservoir-to-surface fault zones and trapped shallow gas pockets.
NEOS was engaged to conduct a 30-square-mile, basement-to-surface Eco-Assurance survey in Western Pennsylvania. Airborne-acquired hyperspectral data revealed surface oil seeps and gas plumes, along with wetlands, waterways and the condition of local botany. Sensors were calibrated to the hyperspectral signatures of hydrocarbons unique to the area, and anomalies were verified via ground truthing.
To continue reading the rest of this case study (or to view more case studies from the Unlock the Potential series), click here.