NEOS recently took on a project to asses the supply source of CO2 used for Enhanced Oil Recovery (EOR) in the northern Raton Basin. Onshore structurally complex areas, such as this, combined with large amount of igneous intrusions can be difficult to image at depth with seismic data alone.
This multi-measurement interpretation study incorporating airborne- and ground-acquired geophysical data covers more than 1,000 square miles of topographically challenging, environmentally sensitive terrain in the Rocky Mountain region, an area containing numerous natural accumulations of CO2.
Join us at the AAPG Technical Program next week to gain more insight into this study.
Mark your calendar: Structural models constrained by geophysical data provide additional insight to the subsurface in Southern Colorado, U.S. (Expanded abstract) M. Soledad Velasco, NEOS
Tuesday, June 21st | 8:25AM
Theme 5 – “Structural Interpretation Quality and Methods”
For more on NEOS’ work in the northern Raton Basin click here for our article “Resistivity imaging in a fold and thrust belt using ZTEM and sparse MT data” from the 2016 April issue of First Break.
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The delivery of an integrated, congruous, and consistent earth model provides geothermal operators with the insights required to make informed field development decisions, including:
Attributed of the geothermal system as a whole
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Characteristics of the geothermal reservoir and fluids
Click here to read more about the NEOS Geothermal Solution.
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.
NEOS identified four distinct play types in the 6,000 sqkm area assessed on the Lebanon neoBASIN project:
A Triassic interval (BLUE) which is geologically similar to the gas and condensate fields of Syria’s Palmyride Belt to the northeast of the survey area;
A deeper (and potentially more gas prone) Paleozoic interval (PURPLE) also analogous to the Palmyride fields;
A Triassic interval in the near-offshore (BRICK RED) which is likely to be gas prone;
A Jurassic interval (YELLOW) which is geologically similar to the oil & gas fields producing south of Lebanon.
The locations on the image above are intentionally disguisedin terms of their geo-spatial locations and size (some of the areas shown above are depicted as being smaller compared to those actually assessed as prospective); actual locations of these highgraded play types would, of course, be revealed to licensees of the Lebanon neoBASIN Knowledge Library.
It is interesting to note that the actual interpretation suggests that several areas are prospective for multiple play types, meaning we have ‘stacked plays’ that should reduce the overall exploration risk in these locations given the possibility of multiple targets.
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?