Geologic Hydrogen
Geophysics for Geologic H2 Exploration
In this series, we aim to illustrate the existing geophysical technologies that can be reconfigured and recombined for geologic hydrogen exploration, as well as present new development in this field. We hope you enjoy the series!
Geophysics for Geologic H2 Exploration Series: No.1
A key component of geologic hydrogen systems is the source rocks, and the most notable type is ultramafics. How do we find and characterize the rocks? Magnetic geophysics with the exploration-scale data offers an effective tool for this purpose. The reason is that ultramafic rocks are magnetic in nature because of their primary magnetite content, and they light up like Christmas trees magnetically, so to speak. Quantitative magnetic techniques developed in mineral exploration can therefore image H2 source rocks effectively. Here we illustrate the capability with an example of 3D magnetic inversion that images an ultramafic flow unit.
Geophysics for Geologic H2 Exploration Series: No.2
Some geologic H2 source rocks may have high magnetic susceptibility that leads to self-demagnetization. This effect makes for an interesting but more challenging problem. Magnetic geophysics can still image such source rocks effectively, but the imaging process is more complicated because of the unknown and variable magnetization direction. Using transformed data such as amplitude anomalies is way to overcome the challenge. Here we illustrate how a banded iron formation (BIF) with high susceptibility is imaged using magnetics, including the arcuate shapes often seen in BIF.
Geophysics for Geologic H2 Exploration Series: No.3
We illustrate the use of gravity geophysics in imaging the depths to the basement rocks. Source rocks are often present in the basement below sedimentary basins, such as the case in eastern Kansas, US. Therefore, mapping the basement structure is a key aspect for H2 exploration. Gravity and magnetic data provide an effective and cost-efficient means to accomplish this over large scales. In this example, we improve upon seismically derived basement relief through a cooperative 3D gravity inversion. What’s shown here is like the Cadillac of gravity imaging for basement because it integrates multiple geophysical data sets.
Geophysics for Geologic H2 Exploration Series: No.4
We illustrate the use of seismic geophysics to predict gas-bearing reservoirs. Seismic surveys can be costly, but the data have high resolution to image the subsurface structure and predict lithologies. The seismic amplitude versus offset (AVO), which may increase, decrease, or switch polarity depending on the lithologies, is a key signature that can be effective in natural hydrogen exploration. AVO can distinguish gas bearing reservoirs from dry strata without gas. It is not easy to directly identify the type of gas based only on seismic data, but ascertaining the presence of gas is the first and necessary step for finding geologic H2 — and the chances increase if there are H2 source rocks nearby.
Geophysics for Geologic H2 Exploration Series: No.5
Gravity gradient data can image subsurface density variations, which are connected to the alteration within H2 source rocks or the structures for potential H2 migration pathways in the sedimentary basins. Modern airborne gravity gradiometry and associated processing and imaging techniques offer an effective suite of tools in geologic H2 exploration. This example from S. Africa illustrate the said capability.
Geophysics for Geologic H2 Exploration Series: No.6
Bright spot, or sweet spot, is a seismic attribute that can predict the presence of H2 in geologic H2 exploration. This example from China illustrates the use of bright spot in identifying the location of a drilled well for natural gas. A critical step is to compare the seismic interpretation with the lithology logs in post-drilling analyses. Integrating well logging from exploratory wells with seismic sections reduces the risk of false positive gas predictions when deciding well locations.
Geophysics for Geologic H2 Exploration Series: No.7
Lithofacies identification, also called geology differentiation, is a multiphysics method that can image the source-rock interior or de-risk drilling for reservoirs in geologic H2 exploration. The method uses distinctive physical property ranges to identify lithologies from the inversion of two or more geophysical data sets. This example from Brazil maps the lithologies in 3D volume from density and magnetic susceptibility volumes and showcases the capability.
Geophysics for Geologic H2 Exploration Series: No.8
Where does geologic hydrogen fit in? The main difference is that blue and green H2 serve as an energy carrier, whereas geologic H2 is a primary energy source. Geologic H2 includes both natural H2 (gold or white) and stimulated H2 (orange), which have an overall zero or negative CO2 emission. Geophysics plays different roles for different types of H2 . We summarize them here and focus on the geologic H2 in our paper: “The role of geophysics in geologic hydrogen resources”.
Geophysics for Geologic H2 Exploration Series: No.9
In addition to its utility in imaging the source rocks in natural geologic H2 exploration, magnetics provides one of several geophysical tools for monitoring stimulated geologic hydrogen production. This synthetic study demonstrates that surface and borehole magnetic data together can resolved vertically stacked zones with increased susceptibilities. This is a far superior result than what is possible by either borehole or surface data alone.
Geophysics for Geologic H2 Exploration Series: No.10
In addition to its utility in imaging the source rocks in natural geologic H2 exploration, magnetics provides one of several geophysical tools for monitoring stimulated geologic hydrogen production. This synthetic study demonstrates that surface and borehole magnetic data together can resolved vertically stacked zones with increased susceptibilities. This is a far superior result than what is possible by either borehole or surface data alone.
Geophysics for Geologic H2 Exploration Series: No.11
Multiphysics and machine learning (ML) integration can play an important role in geologic H2 exploration. Different geophysical data sets provide multifaceted information about source rocks or H2 accumulation, while ML approaches help effectively extract information for decision making. This example from mineral exploration illustrates the strengths of the combination, which are equally applicable to geologic H2 exploration and production monitoring.
