With the year in full swing and several industry events around the corner, we want to remind everyone to not miss your chance to catch our own Dr. Morgan Brown – an expert in seismic depth imaging – presenting at two upcoming events. If you aren’t able to make these events, not to worry; we will upload a recording of Morgan’s presentation in the coming weeks.
2017 3D Seismic Symposium – Wednesday, February 22 in Denver
Organized by the Rocky Mountain Association of Geologists (RMAG) and the Denver Geophysical Society (DGS), this year’s symposium promises a full agenda of informational presentations focused on seismic imaging in North America. Morgan will take the stage at 10:30 AM to present a prestack depth migration case study from the Appalachian Basin/Marcellus-Utica shale.
CSEG Technical Luncheon – Monday, February 27 in Calgary
The following week, Morgan will be presenting at CSEG’s luncheon. The lunch starts at 11:30 at the Calgary Petroleum Club.
About Dr. Morgan Brown Morgan is a well-known evangelist for advanced seismic processing technology including PSDM imaging. As a Geophysical Advisor in Depth Imaging at NEOS, his role includes optimizing PSDM workflows and consulting on internal PSDM projects. Morgan received a Ph.D. in Geophysics from Stanford University and a B.A. in Applied Math from Rice University.
Click here to continue reading this article on the Value of Information that we co-authored with Palantir and which was published in OilVoice on the 1st of September. Palantir used their economic modeling and asset optimization software to determine the economics of Vaca Muerta shale development under four different scenarios, in which the quantity and quality of subsurface G&G information varied.
The conclusion: investing $1,000 per sqkm to acquire and interpret multi-physics data in an attempt to highgrade acreage and identify sweet spots has a 10x ROI and roughly doubles the resource additions from the 30 well program.
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?