SBIR/STTR Research Award

Geothermal Asset Integrity Model

Award identifier a2483866b236b8b9d128c690e944d8b05e31c6ec55221a7419014fbc7c181f69Awarding agency Department of Energy

Award amount

$1,100,000

Program and phase

SBIR · Phase II

Award year

2023

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
OLI SYSTEMS INC
Proposal award date
2023-04-03
Contract end date
2025-04-02
UEI
UCPBBA5GVES1
Solicitation number
Not reported
Topic code
C53-21a

Research abstract

C53-21a-271193Assuring trouble-free performance of downhole and surface components is critical for generation of low- cost electricity from geothermal energy systems. Because geothermal environments can be extremely corrosive, managing the corrosion of alloys used in geothermal system through a combination of proper alloy selection and operational practices is essential. Unfortunately, materials selection and operational guidance for geothermal systems at present are qualitative, and operators work only with lagging indicators of performance. Mineral scaling from geothermal fluids is another major obstacle, fouling devices, wells, and aquifers close to filters, which lowers operating efficiency by decreasing the flow rate from the well and heat transfer efficiency. Scaling also may exacerbate corrosion by acting as a crevice, thereby reducing concentrations of inhibitors that can reach the metal surface. While current models can address aspects of scaling or corrosion, no modeling tool accurately predicts both these problems. OLI Systems proposes an integrated tool to mitigate scaling and corrosion risk in geothermal energy production to lower the cost of geothermal systems. The tool will also be combined with probabilistic assessment and offered as a cloud-based software solution. In Phase 1, the OLI Mixed-Solvent Electrolyte model was refined to model electrochemical kinetics and localized corrosion of alloys and chemistries encountered in geothermal systems. Limited experimental data were used to demonstrate the feasibility of the approach, and the model was validated using existing geothermal corrosion data. Mineral scale prediction for some systems is already available in OLI software. In Phase 2, the corrosion model will be further extended using new experimental data to ascertain the performance of alloys at high temperatures. The model will include alloys representing the broadest range of Corrosion Resistant Alloys likely to be used in geothermal applications. The existing OLI Mixed Solvent Electrolyte thermodynamic model will be enhanced to predict the formation of mineral scales from various crystalline and amorphous forms of carbonates, sulfates, silicates, and sulfides over low to extreme ranges of salinity, temperature, and pressure. An advisory module will be created to convert the detailed model predictions into implementation action items/recommendations, including probabilistic assessment. The model will be incorporated into a cloud platform to enable real-time monitoring and process automation. These new capabilities will enable accurate estimation of technical and financial risk for geothermal energy production to make it more cost-competitive, scalable, and reliable than other alternatives. Broader benefits of the project will include the ability to model electrochemical kinetics in non-aqueous environments involved in energy storage and metal separation, as well as material performance in oil and gas production systems.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

4 SBIR/STTR records share this UEI (2022–2024). Reported award amounts total $1,800,000. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Energy

Agency intelligence

Department of Energy

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.