{"678327":{"#nid":"678327","#data":{"type":"news","title":"Digital Twins Make CO\u2082\u00a0Storage Safer","body":[{"value":"\u003Cp\u003EAs greenhouse gases accumulate in the Earth\u2019s atmosphere, scientists are \u003Ca href=\u0022https:\/\/research.gatech.edu\/feature\/direct-air-capture?utm_source=coe_homepage\u0026amp;utm_medium=web\u0026amp;utm_campaign=newsfeed\u0022\u003Edeveloping technologies\u003C\/a\u003E to pull billions of tons of carbon dioxide (CO2) from the air and inject it deep underground.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe idea isn\u2019t new. In the 1970s, Italian physicist\u0026nbsp;Cesare Marchetti\u0026nbsp;suggested that the carbon dioxide polluting the air and warming the planet could be stored underground. The reality of how to do it cost-effectively and safely has challenged scientists for decades.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EGeologic carbon storage \u2014 the subterranean storage of CO2 \u2014 comes with significant challenges, most importantly, how to avoid fracturing underground rock layers and letting gas escape into the atmosphere. Carbon, a gas, can behave erratically or leak whenever it\u2019s stored in a compressed space, making areas geologically unstable and potentially causing legal headaches for corporations that invest in it. This uncertainty, coupled with the expense of the carbon capture process and its infrastructure, means the industry needs reliable predictions to justify it.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EGeorgia Tech researcher and\u0026nbsp;\u003Ca href=\u0022https:\/\/gra.org\/scholar\/94\/Felix_Herrmann.html\u0022\u003EGeorgia Research Alliance Eminent Scholar\u003C\/a\u003E\u0026nbsp;\u003Ca href=\u0022https:\/\/eas.gatech.edu\/people\/herrmann-dr-felix\u0022\u003EFelix J. Herrmann\u003C\/a\u003E has an answer. His lab,\u0026nbsp;\u003Ca href=\u0022https:\/\/slim.gatech.edu\/\u0022\u003ESeismic Laboratory for Imaging and Modeling (SLIM),\u003C\/a\u003E uses advanced artificial intelligence (AI) techniques to create algorithms that monitor and optimize carbon storage. The algorithms work as \u201cdigital twins,\u201d or digital replicas of underground systems, facilitating the safe, efficient storage of CO2 underground.\u003C\/p\u003E\u003Cp\u003E\u201cThe trick is you want the carbon to stay put \u2014 to avoid the risk of, say, triggering an earthquake or the carbon leaking out,\u201d said Herrmann, professor in the \u003Ca href=\u0022https:\/\/eas.gatech.edu\/\u0022\u003ESchool of Earth and Atmospheric Sciences\u003C\/a\u003E and the \u003Ca href=\u0022https:\/\/ece.gatech.edu\/\u0022\u003ESchool of Electrical and Computer Engineering\u003C\/a\u003E. \u201cWe\u2019re developing a digital twin that allows us to monitor and control what is happening underground.\u201d\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EPredicting the Best Place\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWaveform Variational Inference via Subsurface Extensions with Refinements (WISER) is an algorithm that uses sound waves to analyze underground structures. WISER runs on AI, enabling it to work more efficiently than most algorithms while remaining computationally feasible. To improve accuracy, WISER makes small adjustments using sound wave physics to show how fast sound travels through different materials and where there\u2019s variation in underground layers. This helps to create detailed, reliable images of underground areas for better predictions of carbon storage.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EWISER allows researchers to work with uncertainties, which is vital for understanding the risk of these underground storage projects.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EScaling the Algorithm\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWhile Herrmann\u2019s lab has been working to apply neural networks to seismic imaging for years now, WISER required them to increase the networks\u2019 scale. Making multiple predictions is a much larger problem that requires a bigger, more potent network, but these types of neural networks only run on graphics processing units (GPUs), which are known for speed but are limited in memory.\u003C\/p\u003E\u003Cp\u003ETo optimize the GPU, \u003Ca href=\u0022https:\/\/slim.gatech.edu\/people\/rafael-orozco\u0022\u003ERafael Orozco\u003C\/a\u003E, a computational science and engineering Ph.D. student, created a new type of neural network that can train with very little memory. This open-source package, \u003Ca href=\u0022https:\/\/github.com\/slimgroup\/InvertibleNetworks.jl\u0022\u003EInvertibleNetworks\u003C\/a\u003E, enables the network to train on very large inputs and create multiple output images conditioned on the observed seismic data.\u003C\/p\u003E\u003Cp\u003EWISER\u2019s fundamental innovation is for the lab\u2019s next concept: creating digital twins for carbon storage. These twins can act as monitoring systems to optimize and mitigate risks of carbon storage projects.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDevising the Digital Twin\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDigital twins are dynamic virtual models of objects in the real world, capable of replicating their behavior and performance. They rely on real-time data to evolve and have been used to replicate factories, cities, spacecraft, and bodies, to make informed decisions about healthcare, maintenance, production, supply chains, and \u2014 in Herrmann\u2019s case \u2014 geologic carbon storage.\u003C\/p\u003E\u003Cp\u003EHerrmann and his team have developed an \u201cuncertainty-aware\u201d digital twin. That means the tool can manage risks and make decisions in an uncertain, unseen environment \u2014 because it\u2019s been designed to recognize, quantify, and incorporate uncertainties in CO2 storage.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EProbing the Unseen\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESubsurface conditions are diverse and complex, making the management of greenhouse gas storage a delicate process. Without careful monitoring, the injection of CO2\u0026nbsp;can increase pressure in rock formations, potentially fracturing the cap rock that is supposed to keep the gas underground.\u003C\/p\u003E\u003Cp\u003E\u201cThe digital twin addresses this through simulations in tandem with observations,\u201d said Herrmann, whose team linked two different scientific fields \u2014 geophysics and reservoir engineering \u2014 for a more comprehensive understanding of the subsurface environment. Specifically, they combined geophysical well observations with seismic imaging.\u003C\/p\u003E\u003Cp\u003EGeophysical well observation involves drilling a hole in the subsurface in a geological area of interest and collecting data by lowering a probe into the borehole to take measurements. Seismic imaging, on the other hand, \u0026nbsp;uses acoustic waves to create images based on the analysis of wave vibrations.\u003C\/p\u003E\u003Cp\u003E\u201cBridging the gap between different fields of research and combining various data sources allows our digital twin to provide a more accurate and detailed picture of what\u2019s happening underground,\u201d Herrmann said.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ETo integrate and leverage these diverse datasets built from observations and simulations, the team used advanced AI techniques like simulation-based inference and sequential Bayesian inference, a method of updating information as more data becomes available. The ongoing learning allows researchers to quantify uncertainties in the subsurface environment and predict how that system will respond to CO2 injection. The digital twin updates its understanding as new data becomes available.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EMaking Informed Decisions\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EHerrmann\u2019s team tested the digital twin, simulating different states of an underground reservoir, including permeability, which is the measure of how easily fluids flow through rock. The goal was to find the maximum injection rate of CO2 without causing fractures in the cap rock.\u003C\/p\u003E\u003Cp\u003E\u201cThe work highlights how dynamic digital twins can play a key role in mitigating the risks associated with geologic carbon storage,\u201d said Herrmann, whose research group is supported in part by large oil and gas companies, including Chevron and \u0026nbsp;ExxonMobil. \u201cCompanies are now in the process of starting large offshore projects for which the digital twin is being developed.\u201d\u003C\/p\u003E\u003Cp\u003EBut there is still plenty of work to be done, he added. For instance, the digital twin can monitor the subsurface and provide critical information about that uncertain environment. It can inform. But it still needs adjustments by humans for each new CO2 injection site, and Herrmann and his team are working on further developing the technology \u2014 giving the digital twins the ability to quickly replicate themselves so they can be deployed massively and quickly to meet the demands of mitigating climate change.\u003C\/p\u003E\u003Cp\u003E\u201cOur aim is to make them smarter,\u201d Herrmann said. \u201cTo make them more adaptable, so they can control\u0026nbsp;CO2 injections, become more responsive to risks, and adapt to a wide range of complex situations in real time.\u201d\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAlgorithmic innovations produce multiple models to assess risks of safe carbon storage.\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Algorithmic innovations produce multiple models to assess risks of safe carbon storage."}],"uid":"34541","created_gmt":"2024-11-11 16:43:28","changed_gmt":"2024-12-04 19:17:53","author":"Tess Malone","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2024-11-11T00:00:00-05:00","iso_date":"2024-11-11T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"675570":{"id":"675570","type":"image","title":"wiserdigitaltwins.png","body":"\u003Cdiv\u003EThe top figure shows a geologic area and the seismic survey over that area. Red symbols represent sources, and yellow symbols represent receivers needed to conduct that survey. There are two wells: the left well is injecting CO2 in this area and the right well is monitoring the underground CO2 flow. The bottom figures show the CO2 plume overlaid over two different permeability models. Since permeability is the parameter which defines the ease of flow of any fluid in the subsurface, we can see shape of CO2 plumes are different in the bottom left and right figures. This figure also signifies the importance of monitoring CO2 storage projects because in the bottom right figure we can see that CO2 plume is almost breaching the storage complex which is undesirable for the regulators.\u003C\/div\u003E\u003Cp\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E","created":"1731343442","gmt_created":"2024-11-11 16:44:02","changed":"1731343442","gmt_changed":"2024-11-11 16:44:02","alt":"Figures of how carbon storage works","file":{"fid":"259208","name":"wiserdigitaltwins.png","image_path":"\/sites\/default\/files\/2024\/11\/11\/wiserdigitaltwins.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/11\/11\/wiserdigitaltwins.png","mime":"image\/png","size":505058,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/11\/11\/wiserdigitaltwins.png?itok=IzFKBPXn"}}},"media_ids":["675570"],"groups":[{"id":"1278","name":"College of Sciences"},{"id":"1214","name":"News Room"},{"id":"1188","name":"Research Horizons"},{"id":"364801","name":"School of Earth and Atmospheric Sciences (EAS)"}],"categories":[],"keywords":[{"id":"187915","name":"go-researchnews"},{"id":"193266","name":"cos-research"},{"id":"192254","name":"cos-climate"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EWriters: Jerry Grillo and Tess Malone\u003C\/p\u003E\u003Cp\u003EMedia Contact: Tess Malone | tess.malone@gatech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}