Many thanks to our friends at Scripps and ConocoPhillips for this really terrific satellite-derived gravity image of the ocean floor! To read the article, click here.
The NEOS MMI methodology, specifically with the use of potential methods, is greatly suited to provide understanding of the structural complexity of a basin, at the basement level.
While gravity and magnetic methods use different rock properties (density vs. susceptibility), these methods are diagnostic and when taken together can eliminate many geologic alternative scenarios therefore putting constraints on geologic models.
In oil and gas exploration, the understanding of depth and structural configuration of basement plays a significant role. The depth-to-basement estimates from gravity and magnetic data lead to an estimate of thickness, depth of burial and thermal maturity of a horizon of interest. These parameters are very important in modeling and determination of hydrocarbon generation. In addition, the understanding of basement structure leads to the understanding of global plate tectonics. Many of the world’s rift basins and spreading centers are recognized based on the magnetic data, two examples are the Red Sea Rift basin and Mid-Atlantic Ridge.
Magnetic data also typically highlights the changes in composition of the basement rock that would lead to differential thermal conductivity and thermal maturity of the source rock. In some recently surveyed areas, NEOS Geoscientists were able to relate enhanced production in shales based on its thermal maturity due to differential basement lithology in the area.
Click here to learn more on NEOS’ Basement Applications of Multi-Measurement Interpretation. For a better understanding of MMI methods throughout the entire geologic column watch the narrated slideshow.
A multi-physics approach to geoscience allows NEOS to simultaneously interpret several possible geophysical measurements in order to uncover deeper insights into regional prospectivity and well productivity. While there may be potential for the inclusion of a number of measurements within an interpretation, each is equally unique and beneficial on its own accord.
GRAVITY & MAGNETICS – A PART OF MMI
NEOS incorporates gravity and magnetics in all neoBASIN programs, as these measurements are fundamental to the company’s multi-measurement interpretation (MMI) methodology. Gravity and magnetic data is acquired, along with other MMI measurements, using airborne systems simultaneously in a fast, efficient and non-invasive way, which reduces the turnaround time for the data acquisition, integration and interpretation. The data collected gives NEOS insight into the subsurface over large regional, basin-scale areas or at the more detailed, prospect level.
Gravity and magnetic methods are commonly referred to as potential field methods because the measurements involve a function of the potential of the observed field of force (gravity or magnetic). The data is used to help delineate geologic features in the Earth’s upper crust related to lithologic changes caused by natural hazards (faults, volcanoes), natural resources (gas, minerals) and tectonic events such as the formation of mountain belts.
These measurements take advantage of the variation in different lithologic characteristics of subsurface rock in a given area and can quickly and easily map location, extent, depth and structure of sedimentary basins. In addition, these methods can quickly identify faults, mineral deposits, igneous intrusive and extrusive, and depth-to-crystalline basement.
While typically grouped together, it’s still important to understand how each functions, so let’s look at gravity and magnetics individually.
Gravity measures very small variations (anomalies) of the Earth’s gravitational field that are caused by lateral variations in the density of Earth material.
Specifically, gravity data is useful whenever the formation(s) of interest have densities that are different from surrounding formations. There is a wide range of densities within the Earth’s crust, from essentially zero density of air-filled voids in near-surface formations to the highest densities related to iron/magnesium-rich basement rocks and metallic ores. Because of the wide range of densities within all rock types, geoscientists interpret measurements and draw conclusions regarding the distribution of underground rock types that may be commonly favorable to trapping oil or gas. A typical gravity survey will map sedimentary basin configuration, structure and thickness, and faults. It will also map basement configuration where basement rocks are of higher density than sedimentary section, and salt bodies and distribution.
For example, salt has a very low density of 2.15. The identification of a salt dome would help to locate possible oil and gas reservoirs as many oil and gas deposits are located along the structures caused by salt movement within the sedimentary basin. A typical example of this is the large oil and gas reservoirs along the Gulf of Mexico.
The magnetic field of the Earth is generated by electrical currents in the liquid outer core. Rocks that have high magnetite content typically have the property ideal for magnetization, also known as susceptibility. Magnetic data measures the minute changes in a rock’s magnetic response caused by contrast in the susceptibility after an external magnetic field is removed. Field data responds to tectonic fabric, due to the redistribution of magnetite rich rocks and is typically used in mapping basement structure or the thickness of sedimentary section.
Faults and fractures are easily detected by magnetic method due to mineralization along fault planes. This method is widely used in the exploration and distribution of mineral deposits containing magnetite. In oil and gas exploration, magnetic method is used in determination of depth-to-basement, fault detection and distribution, basement rock type leading to recognition of differential thermal conductivity or the thermal maturity of a basin.
In the field of regional exploration, magnetic data is useful in delineating crystalline basement structures and tectonic elements as rift basins and basement involved tectonic elements. It also can delineate the distribution of volcanic material, both intrusive and extrusive. Recently, NEOS has used magnetic data to look for changes in basement lithology and successfully related it to enhanced production in overlying shales.
Click here for more detail on gravity and magnetic measurements.
While it’s true that we’re dealing with the same measurements – gravity and magnetic – the quality and utility of the public data can vary greatly depending on how the measurements were acquired. For one thing, public datasets are often acquired at fairly sparse line spacing – often 5-10km. Moreover, the public measurements might have been acquired using ground-based acquisition stations. If this is the case, not only is the ‘cross-line spacing’ going to be 5-10km, so too will be the ‘in-line’ spacing.
In the case of the Grav-Mag datasets that NEOS typically acquires for a neoBASIN survey, the cross-line spacing will be much tighter; our standard flight-line spacing is 1km. The in-line sampling density will be even greater, as the aircraft we use are capturing measurements roughly every 80 meters for gravity (1Hz sampling) and every 8 meters for magnetic (10Hz sampling).
The results become visible in the panel of images above. The upper panel shows the (Tilt Derivative of) Magnetic data, while the bottom panel shows the (First Vertical Derivative of) Gravity data. On the right side is the data we actually acquired for our neoBASIN project in and around Venango County, Pennsylvania. The black lines are faults and lineaments that were interpreted based on an analysis of not only these two derivative products of the Grav-Mag datasets, but also of a suite of roughly 15 direct Grav-Mag measurements and associated attributes and derivatives that were extracted from them.
We then decimated the actual datasets back to 5km (middle panels) and 10km (far left panels) flight-line spacing and reinterpreted the datasets (and the associated attributes and derivatives) to identify the faults and lineaments we felt were present. Hopefully you can see the improvements in not only resolution, but also in the number of interpreted faults and lineaments, as one moves from left to right.
And these are still best case differences – we didn’t decimate the datasets in-line; had we done so, the middle and left side data quality (and fault interpretations) would be even worse.
It is for the reasons shown here that we often recommend that our clients acquire new Grav-Mag data as part of a neoBASIN regional program even if they have access to publicly available measurements. After all, who would want to take the risk of drilling and fracing a $10 million well using “left panel data” when only 1/3 of the faults in the area have been identified?