Part VI
Now it is time to gear up and fast-forward to the subject of natural hydrogen reconnaissance and exploration.
We Avalio founders have been ingeminating for years that natural hydrogen is quite different in its physical and chemical properties from petroleum, methane in particular. Consequently, natural hydrogen reconnaissance and exploration methods shall be different from those for oil and gas, as well as for mining/minerals.
(NB: Please note that we do not refuse the time-proven methods usability, as a whole. Physics is physics, after all. All we are humbly saying that in order to be useful, these techniques have to be applied differently, with conscious awareness of hydrogen differences from petroleum and mineral resources these methods were originally developed for).
Nonetheless, the community knows better, obstinately attempting to copy-paste petroleum or minerals exploration algorithms and one-to-one apply them to natural hydrogen.
As a result, lots of money have been – and still – wasted. Despite the unconvincing – I hate to say mediocre – results of such campaigns, operators keep repeating the same errors over and over, with a tenacity that deserves better application. (Looks like there is a “critical mass” of losses and mis-steps that needs to be accumulated before the towel is thrown and the switch is flipped, enticing the analytical process. Proactive thinking seems to be out of fashion these days, alas).
One of the most popular ways is to utilize conventional seismic methods for natural hydrogen exploration – with no particular customization seemingly being attempted in order to account for the differences between natural hydrogen and petroleum resources mentioned above and earlier (Part I, Part II, Part III, Part IV, Part V). The most frequently verbalized reason for this is that “it works OK for natural gas, so it should be sufficient for natural hydrogen too.” This approach is rooted all the same where the reasoning for drilling for natural hydrogen “reservoirs” is coming from: someone’s beliefs and wishful thinking, i.e. “the Dreamland”.
There are several problems with this approach:
1) Unlike methane, natural hydrogen does not reside in sub-lateral, dome-like structures (see Part IV, Part V), which the conventional seismic methods were originally developed for (see the title illustration at the beginning of this piece);
2) Seismic methods are not capable of telling the trapped fluids composition – so how would it be possible to find our that the reservoir contains hydrogen???
3) Even if items 1) and 2) above materialized, the replenishment is the key. Alas, the latter is impossible to be determined when the conventional seismic is used “as is”.
Here, I can see the flaming script on the wall: “OK OK suppose you are right… So what’s the solution?”
“No worries, mate” as people say in my hereabouts. Since we all (hopefully) agreed (???) that natural hydrogen migrates in (sub)vertical dynamic flows, then the solution we seek must address this peculiarity, right? Provided that conventional seismic does not allow “seeing” (sub)vertical tectonic and structural dislocations, then there is need for some algorithm that would resolve this deficiency. What could it be?
TA-DAMMM!!! Oil and gas industry throws us the lifeline here, again – although a very un-orthodox one. About 30 years ago, the Duplex Wave Migration, or DWM, was developed in order to assist with exploring reef reservoirs, which represent a sort of a mix-breed between the “trap” and the “migration path” (please excuse me this simplification here if you find one). The result: (sub)vertical geological structures between 60° and 90° that always been interpretative on conventional seismic images, i.e., susceptible to a human error – now can be clearly distinguished and, more importantly, digitized and synthesized into the math model of the potential target (Fig. 1 below).
This hidden gem of exploration geophysics* is readily available for other tasks, offered by Tesseral AI based in Calgary, Alta. Brian Schulte, my colleague and a personal friend, is at your disposal to provide you with his outstanding professional assistance and guidance, please love and respect.
Fig. 1. Subvertical fault deciphered by conventional seismic (top) vs. DWM (bottom).
Subject to data array meeting certain criterion, the DWM tool allows to semi-quantify the (supposedly) target structures’ conveying activity by means of fluid dynamics, which allows ranking them for potential productivity (Fig. 2).
Fig. 2. Seismic 2.5D Image of Sub-Vertical Structures.
The cherry on the cake: DWM could be used for re-migrating and re-interpretation of the EXISTING seismic data arrays, provided this “raw” data meets resolution and signal density. This could save an operator a buck or two through obtaining new information from data acquired earlier.
Another frequent but not necessarily correct practice is to use the existing or even shoot new magnetics and gravity surveys, with the preference given to the aerial ways of acquiring data. The theory behind it is so-called “ferrolysis”, which was reviewed in quite detailed way in Part III. However, if assessed from the PHE concept viewpoint, it becomes clear that hydrogen, in the process of its journey towards the surface, may or may not pass geological objects possessing high magnetic and gravity values, i.e., containing iron. In other words, hydrogen flowing upwards could not care less what rocks it meets on its way – it either bypasses them ow flows through them. Consequently, in the light of PHE, these methods lose their attractiveness for natural hydrogen exploration, becoming subtle and secondary. They may be used as an additional source of data for building geological model, but not as a primary one for pinpointing the actual “deposit” or “source” of hydrogen.
As of today, there is no actual proof that conventional seismic or gravity or magnetic surveys have ever practically assisted in discovering commercial resources (flows) of natural hydrogen.
Whether the above geophysical methods are worth spending valuable funding on – this is entirely up to you, my dear peers. Just bear in mind that your investor/s may actually read this piece and then start asking you discomfortable questions.
(Once again, please don’t shoot the messenger, all I am trying to do is to help avoiding painful and costly mistakes).
*DFM is not the only tool in the Tesseral AI toolbox. Full-Wave Modeling is another mighty means for revealing the Mother Earth’s treasures and resolving its riddles.
Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of Energy News. This content is presented as the author’s analysis based on available information at the time of writing. It should not be considered as representative of Energy News or its editorial stance. Readers are encouraged to consider this as one perspective among many and to form their own opinions based on multiple sources.
