Brixton Metals Commences Drilling at its Thorn Copper-Gold Project
2025 Thorn Exploration Plan Highlights:
The 2025 exploration plan consists of 8,000 to 10,000 meters of drilling across several target areas and is split between gold and copper targets as previously stated in the news release dated May 6, 2025.
CLICK HERE for a 3D presentation of the Thorn Project.
Chairman and CEO Gary R. Thompson stated, 'We are excited to have the drills turning again at the Thorn Project. Between the new gold mineralization and copper porphyry discovery potential, we are in for an interesting exploration season.'
Figure 1. Thorn Project Gold Geochemistry Map.Camp Creek Feeder Structures
High-sulphidation style gold mineralization is located near surface, these zones are interpreted as potential feeder structures. Three holes, 307, 221, and 294 encountered gold mineralization that appear to have a northeast trend, which is parallel to the Camp Creek structural corridor where drilling is planned to test the continuity of this structure. Hole 307 returned 26m of 1.89 g/t gold, 74.8 g/t silver, 0.28% copper from 172m depth including 8.00m of 4.52 g/t gold, 148.6 g/t silver, 0.54% copper (Targets in the Figure 2 below). Shallow drilling is planned to test the up-dip gold zone encountered in hole 221 that returned 55.8 g/t gold over 1.5m from 449.5m depth. Based on the success of the initial drilling further holes may be drilled in the area.
Figure 2. Camp Creek Shallow Gold Targets High-Sulphidation Feeder Structures.Figure 3. Photograph of Drill at Site THN25-315 on Old Burn Area of Camp Creek.Trapper Gold Target Drilling
The most significant drill intercept in 2024 was recorded in hole THN24-304, yielding broad intervals of gold mineralization, which included several high-grade sub-intervals assaying 82.00m of 1.27 g/t gold, including 27m of 3.49 g/t gold, including 8m of 11.37g/t gold and including 2.00m of 44.43 g/t gold. In 2022, hole THN22-205 intercepted numerous visible gold counts reporting a drill intercept of 64.00m of 5.74 g/t gold, including 52.00m of 6.97 g/t gold and including 28.95m of 10.36 g/t gold. Follow up drilling is planned to extend this near surface gold mineralization.
Figure 4. Trapper Gold Target Areas, Drilling and Rocks Samples on Magnetic CVG.Catalyst Target
The Catalyst showing, located 6 km northeast of the Camp Creek Porphyry Target, is defined by a 300m long exposure consisting of stockwork quartz-chalcopyrite-molybdenite A veins hosted within a strong quartz-sericite-pyrite alteration zone. The showing is located within a broader 1.6 km by 1 km northeast trending alteration zone hosting phyllic to argillic assemblages, which transitions into a broader area of propylitic alteration. Rock samples from the Catalyst showing returned up to 0.56% Cu, 0.11% Mo, 2.87 g/t Au, and 30.0 g/t Ag, including a 1.55 m chip across a stockwork vein zone which assayed 0.46% Cu, 68 ppm Mo, and 0.37 g/t Au.
Figure 5. Catalyst Target Geology, Principal Components and Soil GeochemistryA Cu- Mo-Ag-Au soil anomaly surrounds the area of exposed quartz-chalcopyrite-molybdenite veins. The location of the soil anomaly is straddling the contact between a Late Cretaceous diorite porphyry and mafic volcanic rocks of the Late Triassic Stuhini Group. A TMI high from the 2010 VTEM survey lies to the northwest of the sample grid where the Cu-Mo anomalies remain open.
Qualified Person
Mr. Gary R. Thompson, P.Geo., is a Director, Chairman, CEO and President for the Company who is a qualified person as defined by National Instrument 43-101. Mr. Thompson has verified the referenced data and analytical results disclosed in this press release and has approved the technical information presented herein.
Corporate Update
The Company has granted an aggregate of 4,300,000 Incentive Stock Options to officers, directors, employees and consultants to the Company at a per share price of $0.10 for a period of ten years from the date of grant. The options are subject to a 12-month vesting period until May 26, 2026.
About Brixton Metals Corporation
Brixton Metals is a Canadian exploration company focused on the advancement of its mining projects. Brixton wholly owns four exploration projects: Brixton's flagship Thorn copper-gold-silver-molybdenum Project, the Hog Heaven copper-silver-gold Project in NW Montana, USA, which is optioned to Ivanhoe Electric Inc., the Langis-HudBay silver-cobalt-nickel Project in Ontario and the Atlin Goldfields Project located in northwest BC which is optioned to Eldorado Gold Corporation. Brixton Metals Corporation shares trade on the TSX-V under the ticker symbol BBB, and on the OTCQB under the ticker symbol BBBXF. For more information about Brixton, please visit our website at www.brixtonmetals.com.
On Behalf of the Board of Directors
Mr. Gary R. Thompson, Chairman and CEO
For Investor Relations inquiries, please contact: Mr. Michael Rapsch, VP Investor Relations. email: michael.rapsch@brixtonmetals.com or call: 604-630-9707
Neither the TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.
Information set forth in this news release may involve forward-looking statements under applicable securities laws. Forward-looking statements are statements that relate to future, not past, events. In this context, forward-looking statements often address expected future business and financial performance, and often contain words such as 'anticipate', 'believe', 'plan', 'estimate', 'expect', and 'intend', statements that an action or event 'may', 'might', 'could', 'should', or 'will' be taken or occur, including statements that address potential quantity and/or grade of minerals, potential size and expansion of a mineralized zone, proposed timing of exploration and development plans, or other similar expressions. All statements, other than statements of historical fact included herein including, without limitation, statements regarding the use of proceeds. By their nature, forward-looking statements involve known and unknown risks, uncertainties and other factors which may cause our actual results, performance or achievements, or other future events, to be materially different from any future results, performance or achievements expressed or implied by such forward-looking statements. Such factors include, among others, the following risks: the need for additional financing; operational risks associated with mineral exploration; fluctuations in commodity prices; title matters; and the additional risks identified in the annual information form of the Company or other reports and filings with the TSXV and applicable Canadian securities regulators. Forward-looking statements are made based on management's beliefs, estimates and opinions on the date that statements are made and the Company undertakes no obligation to update forward-looking statements if these beliefs, estimates and opinions or other circumstances should change, except as required by applicable securities laws. Investors are cautioned against attributing undue certainty to forward-looking statements.
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According to Precedence Research, the AI in oil and gas market size is expected to be worth USD 25.24 billion by 2034, increasing from USD 7.64 billion in 2025 and is projected to grow at a solid CAGR of 14.2% from 2025 to 2034. Oil and gas firms accelerate their digital transformation, and artificial intelligence (AI) is emerging as a game-changer in the sector. Ottawa, Aug. 04, 2025 (GLOBE NEWSWIRE) -- In terms of revenue, the global artificial intelligence (AI) in oil and gas market was valued at USD 6.69 billion in 2024, grew to USD 7.64 billion in 2025. It is predicted to rise from USD 8.73 billion in 2026 to approximately USD 25.24 billion by 2034. This surge is driven by the need for enhanced safety, predictive maintenance, and cost-efficiency in high-stakes operations. In terms of CAGR, the market of AI in oil and gas is expanding at a double-digit CAGR of 14.2% from 2025 to 2034. The growing demand for enhancing operational efficiency in the sector drives the market growth. Note: This report is readily available for immediate delivery. We can review it with you in a meeting to ensure data reliability and quality for decision-making. Try Before You Buy – Get the Sample Report@ Artificial Intelligence in Oil and Gas Market Overview & Insights: The AI in Oil and Gas Market is rapidly evolving as energy companies seek to enhance operational efficiency, safety, and profitability in a volatile and resource-intensive industry. AI technologies such as machine learning, computer vision, natural language processing, and predictive analytics are being integrated across upstream, midstream, and downstream segments to improve decision-making, reduce human error, and lower costs. In upstream exploration and drilling, AI is enabling faster seismic data interpretation, reservoir modeling, and real-time drilling optimization. In midstream operations, AI supports predictive maintenance of pipelines, logistics optimization, and failure detection in transport systems. In the downstream segment, AI enhances refining processes, automates quality control, and personalizes customer engagement at retail fuel stations. AI is no longer a luxury but a necessity in the oil and gas industry,' said Shivani Zoting, Principal Consultant at Precedence Research. 'With growing pressure to optimize costs and reduce downtime, companies are aggressively adopting AI for predictive maintenance and operational automation. How is AI Being Utilized in Oil & Gas Industry? Artificial intelligence in the oil & gas sector is a process of using AI technologies in the oil & gas sector to enhance sustainability, efficiency, and safety. Artificial intelligence is used in various processes like distribution, exploration, refining, and many more in the oil & gas sector. AI helps in identifying potential oil & gas reserves by analyzing seismic data. AI is widely used in various applications like defect detection, drilling optimization, and supply chain optimization in the oil & gas sector. AI helps in increasing efficiency, enhancing productivity, reducing energy consumption, improving safety, making better decisions, and enhancing sustainability. Artificial Intelligence Use in Oil & Gas Companies Company Name AI Use ExxonMobil Predictive Maintenance Reservoir Management Safety Monitoring Royal Dutch Shell Predictive Maintenance Oil & Gas Exploration Chevron Predictive Maintenance Optimizing Cargo Loads and Routes During Transportation British Petroleum Increase Operational Efficiency Producing Geological Data Saudi Aramco Field Monitoring Flare Monitoring Reservoir Modelling ➤ ️ Case Study: Chevron's Predictive AI Transformation in Oilfield Operations Chevron Corporation, a global energy giant, has long been at the forefront of technological innovation in the oil and gas sector. Faced with challenges including fluctuating oil prices, aging infrastructure, and a mandate for enhanced safety and environmental compliance, Chevron invested heavily in Artificial Intelligence starting in 2021. Their goal: to transform upstream operations through predictive insights, real-time monitoring, and optimization. AI Deployment Strategy Chevron partnered with tech leaders such as Microsoft (Azure AI) and to build an enterprise AI platform capable of ingesting real-time data from thousands of IoT sensors embedded across its wellheads, compressors, pipelines, and rigs. Key AI Technologies Used: Predictive Maintenance via machine learning to detect early signs of equipment wear and tear. Digital Twin Models for simulating oilfield performance. Natural Language Processing (NLP) to extract insights from unstructured technical reports. Deep Learning Algorithms to enhance seismic data interpretation and reservoir modeling. Implementation and Impact Pilot Deployment:In 2022, Chevron deployed AI-driven predictive maintenance at its Permian Basin field—a highly productive but complex oilfield in Texas. Measurable Outcomes: Reduced unplanned equipment downtime by 25% in the first year. Extended equipment life cycles by 18%, saving millions in deferred capex. Achieved 15% improvement in overall production efficiency through real-time optimization. Reduced methane leaks and improved compliance by using AI-powered drone inspections and infrared imaging. Broader Transformation The success in the Permian Basin led to enterprise-wide rollout by 2024: AI is now integrated into cargo route optimization, refining processes, and supply chain demand forecasting. Chevron reports an estimated $900 million in operational savings over 3 years, directly attributed to AI initiatives. 'AI allows us to make better decisions, faster—turning billions of data points into actionable insights that protect people, the planet, and profitability.'— Jay Johnson, EVP, Upstream, Chevron Lessons for the IndustryAI is not a plug-and-play solution; it requires robust data infrastructure, skilled talent, and change management. The highest ROI is seen when AI is aligned with core operational KPIs like uptime, safety, and yield. Partnerships with tech vendors and open data ecosystems accelerate innovation. AI is Reshaping the Future of Oil & Gas—Are You In? Join the wave of innovation transforming the energy industry.➡️ Become a valued research partner with us ➢ Artificial Intelligence in Oil and Gas Market Opportunity: What is the Opportunity for Artificial Intelligence (AI) in Oil and Gas Market? Supply Chain Management Unlocks Opportunity The increasing focus on transforming the supply chain management of the oil & gas sector increases the adoption of AI. It provides insights into logistic planning, demand forecasting, and inventory management that help in optimizing supply chain operations. The focus on better customer satisfaction, improving efficiency, and reducing costs fuels demand for AI. The need for identifying disruption in the supply chain increases the adoption of AI's predictive analysis. It analyses market trends, past data, and weather patterns, and helps in avoiding shortages. It helps in supply chain management from upstream operations to distribution, which supports market growth. The growing need for resource allocation, optimization of transportation routes, and scheduling requires AI. The increasing focus on real-time visibility of supply chains fuels demand for AI. Supply chain management creates an opportunity for the growth of the artificial intelligence oil & gas market. Artificial Intelligence (AI) in Oil and Gas Market Challenges and Limitations: What is the Limitation for Artificial Intelligence (AI) in Oil and Gas Market? High Implementation Cost Limits Adoption of AI in Oil & Gas Market Despite several benefits of AI in the oil & gas sector, the high implementation cost restricts the market growth. Factors like the requirement of data management, acquisition, & integration, need for specialized expertise, cybersecurity challenges, and integration with systems require high implementation cost. The analysis, collection, and storage of data requires a data management & infrastructure system that increases the implementation cost. The need for expertise in software development, data science, and machine learning leads to higher implementation costs. The integration with legacy systems requires modifications and upgrades, which increases the cost. The risk of cybersecurity requires monitoring and robust security measures, leading to higher implementation costs. The need for high costs for system integration, hardware, and software directly affects the market. The high implementation cost hampers the artificial intelligence (AI) in the oil & gas market. AI in Oil and Gas Market Coverage: Report Attributes Key Statistics Market Size in 2024 USD 6.69 Billion Market Size in 2025 USD 7.64 Billion Market Size in 2030 USD 14.84 Billion Market Size in 2032 USD 19.35 Billion Market Size by 2034 USD 25.24 Billion Growth Rate (2025 to 2034) CAGR of 14.2% Leading Region in 2024 North America (captured 39.13% of market share) Base Year 2024 Forecast Period 2025 to 2034 Segments Covered Component, Function, Application and Region Regions Covered North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa Key Players Microsoft Corporation, FuGenX Technologies Pvt. Ltd, IBM Corporation, Google LLC, NVIDIA Corp., Royal Dutch Shell PLC, PJSC Gazprom Neft, Huawei Technologies Co. Ltd, Intel Corporation, Neudax, Infosys Limited, and Others. ➡️Become a valued research partner with us - Artificial Intelligence in Oil and Gas Market Key Regional Analysis: Which Region Dominated the Artificial Intelligence (AI) in Oil & Gas Market? North America dominated the Artificial Intelligence (AI) in Oil & Gas Market in 2024. The well-established infrastructure for the extraction of oil & gas increases demand for AI solutions. The growing private companies and government investment in research & development in the oil & gas sector for the implementation of AI help the market growth. The growing production of oil & gas increases demand for AI solutions. The focus on enhancing operational efficiency and optimizing production and exploration in the oil & gas sector fuels demand for AI, driving the overall growth of the market. U.S. AI in Oil and Gas Market Size and Forecast 2025 to 2034 How Big is the U.S. AI in Oil and Gas Market? According to Precedence Research, the U.S. artificial intelligence (AI) in oil and gas market size was valued at USD 1.84 billion in 2024 and is estimated to grow from USD 2.12 billion in 2025 to USD 7.34 billion by 2034. The market is poised to grow at a CAGR of 14.8% from 2025 to 2034. Why U.S. Stands Out: Dominated by innovation and early AI adoption across upstream, midstream, and downstream operations. Proven applications include predictive maintenance, real-time drilling analytics, reservoir modeling, and operational automation. Leading contributions from tech-forward energy companies such as Chevron, ExxonMobil, SLB, and early rollout of platforms like IBM Watsonx in 2024. Adoption and Industry Impact in the U.S. The oil industry is allocating approximately USD 3.1 billion in AI spending in 2024, representing under 5% of total capital expenditures. AI investment is projected to increase up to 80% within five years. (Source: At CERAWeek 2025, U.S. firms like BP, Devon Energy, and Chevron showcased improved productivity thanks to AI: Devon reported a 25% increase in well lifespan, while Chevron uses AI‑driven drones for maintenance and monitoring. (Source: The Complete Study is Now Available for Immediate Access | Download the Sample Pages of this Report@ Interested in how AI can transform your oil & gas operations? Schedule a personalized briefing or request custom data insights tailored to your business goals. ✚ Contact us at or visit ➤ Why is Asia Pacific Growing in the Artificial Intelligence (AI) in Oil & Gas Market? Asia Pacific is experiencing the fastest growth in the market during the forecast period. The increasing production activities and exploration in the oil & gas industry increase demand for AI solutions. The focus on digital transformation in the oil & gas sector fuels the adoption of AI solutions to improve operational efficiency. The increasing demand for cost savings and productivity gains helps in the market growth. The demand for reducing downtime, potential equipment failures, and proactive maintenance increases the adoption of AI solutions. The increasing optimization of operations like refining, drilling, and production increases demand for AI solutions. The growing adoption of AI across applications like downstream, upstream, and midstream drives the overall growth of the market. Artificial Intelligence (AI) in Oil and Gas Market Segmentation Analysis Component Analysis: Why did Software Dominate the Artificial Intelligence (AI) in Oil & Gas Market? The software segment dominated the Artificial Intelligence (AI) in oil & gas market in 2024. The presence of large amounts of data through diverse sources like seismic surveys, sensors, and drilling operations increases demand for software to identify correlations, patterns, and anomalies. The need for automating repetitive tasks like equipment monitoring, data entry, and report generation in the oil & gas sector increases demand for AI software. The focus on extending critical equipment lifespans, preventing unexpected downtime, and reducing maintenance costs requires AI software. The growing demand for software for applications like ensuring compliance, monitoring worker safety, and detecting potential hazards drives the market growth. Function Analysis: How Predictive Maintenance Segment Held the Largest Share in the Artificial Intelligence (AI) in Oil & Gas Market? The predictive maintenance segment held the largest revenue share in the Artificial Intelligence (AI) in oil & gas market in 2024. The focus on minimizing unplanned downtime in the oil & gas sector increases demand for predictive maintenance. The increasing demand for extending the lifespan of equipment and identifying issues of equipment early increases the adoption of predictive maintenance. The focus on minimizing disruptions during planned downtime requires predictive maintenance. The increasing demand for predictive maintenance for optimizing maintenance schedules and enhancing operational efficiency in the oil & gas sector supports the overall growth of the market. Application Analysis: How Application Segment Dominates Artificial Intelligence (AI) in Oil & Gas Market? The upstream segment dominated the Artificial Intelligence (AI) in oil & gas market in 2024. The growing demand for predictive equipment failures, improving operational efficiency, optimizing drilling, and reducing downtime in upstream applications increases demand for AI. The growing focus on extracting and finding oil & gas fuels adoption of AI. The growing utilization of AI functionalities like predictive maintenance in the upstream applications supports the market growth. Related Topics You May Find Useful: ➡️ Oil and Gas Analytics Market: Uncover how data-driven insights are optimizing operations and reducing costs ➡️ AI in Energy Market: Explore how artificial intelligence is transforming grid efficiency and demand forecasting ➡️ Oil and Gas Security Market: See how digital threats are reshaping risk management in critical energy infrastructure ➡️ Oil and Gas Carbon Capture and Storage Market: Track how decarbonization mandates are driving CCS technology investments ➡️ Digital Oilfield Market: Analyze how automation and IoT are redefining exploration and production workflows ➡️ Geospatial Analytics & AI Market: Discover how satellite data and AI are enhancing environmental and asset intelligence ➡️ Industry 4.0 Market: Understand how smart manufacturing is accelerating digital transformation across sectors ➡️ AI in Renewable Energy Market: Gain insight into how AI is powering forecasting, grid stability, and green energy adoption Artificial Intelligence (AI) in Oil and Gas Market Top Companies Microsoft Corporation FuGenX Technologies Pvt. Ltd IBM Corporation Google LLC NVIDIA Corp. Royal Dutch Shell PLC PJSC Gazprom Neft Huawei Technologies Co. Ltd Intel Corporation Neudax Infosys Limited Recent Developments In September 2024, Huawei launched an AI application for oil & gas upstream. Innovation aims to increase production & reserves, achieve high-quality development, enhance industrial quality with intelligence, and ensure safe operations. The focus is on enhancing security, reducing cost, and boosting operational efficiency. (Source: In September 2024, APA Corporation collaborated with Palantir to use AI technology for oil & gas operations. The Palantir focuses on the development of software for supply chain management, production optimization, operational planning, maintenance planning, and contract management. The company's AI solution helps in optimizing raw material logistics, improving equipment reliability, and AIP in invoice & contract documents. (Source: In July 2024, Indosat launched AI solutions for the upstream oil & gas industry. The solution is cloud-based and helps in predictive maintenance for equipment and condition-based monitoring. The solution is used to improve collaborations among workers and monitor workplace safety. (Source: Artificial Intelligence (AI) in Oil and Gas Market Segments Covered in the Report By Component Software Hardware Services By Function Predictive Maintenance Machinery Inspection Material Movement Production Planning Field Services Quality Control Reclamation By Application Upstream Midstream Downstream By Region North America U.S. Canada Europe Germany UK France Italy Spain Sweden Denmark Norway Asia Pacific China Japan India South Korea Thailand Latin America Brazil Mexico Argentina Middle East & Africa South Africa UAE Saudi Arabia Kuwait Thank you for reading. 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