Join AspenTech, now part of Emerson, for a full day of technical presentations, networking opportunities and a happy hour as we showcase our subsurface vision and roadmap.

In today's challenging and rapidly evolving energy environment, the ability to make critical exploration and production decisions hinges on accurate data and robust subsurface models.

Discover how AspenTech Subsurface Science & Engineering solutions help the energy industry deliver secure, sustainable, and affordable energy at lower cost and with fewer emissions.

Seismic inversion of rock properties is crucial for geoscientists assessing the integrity of reservoirs and surrounding formations. Geophysicists face challenges such as limited seismic data resolution, structural complexity and the need for high-productivity technology to meet project deadlines.

AspenTech Industrial AI™는 공정 산업의 판도를 바꾸는 기술로서 AI 알고리즘의 속도와 성능에 실제 도메인 전문 지식의 효율성과 매개변수를 결합하였습니다. 특수 목적에 맞게 설계된 아스펜테크의 AI 솔루션은 데이터 인사이트, 엔지니어링 기반기술, 공정자산에 대한 지식 및 산업에 특화된 전문 지식을 결합하여 고객 기업이 끊임없이 변화하는 비즈니스 요구 사항에 더 빠르게 적응하고 대응할 수 있도록 지원합니다.

The characterization of reservoir fractures poses significant challenges for onshore well planning and hydrocarbon production.

Dr. Bruno de Ribet, an expert in the oil and gas E&P industry, explains how machine learning and Industrial AI have led to deeper insights into relationships in geological data, helping to understand the risks and prospectivity of reservoirs.

Learn how AspenTech University can help organizations to navigate challenges and compete at the highest level with our end-to-end competency development curriculum. AspenTech University offers flexible, expert-led classes that teach the in-depth knowledge and skills required to fully apply AspenTech solutions. Learn by solving real-world problems through hands-on exercises.

The future of the upstream industry lies in the adoption of innovative geoscience digitalization solutions to optimize operations. Machine learning applications for geoscience data have been in use for more than 25 years but have recently become critical due to massive growth in the amount of petrotechnical data being acquired. As machine learning evolves, it will play an increasingly visible role in analyzing surface and subsurface data.

The upstream oil and gas exploration and production industry is looking for ways to reduce costs while minimizing emissions, water use and other environmental impacts. Near-field exploration and development enables producers to leverage already depreciated costs in operating infrastructure and extend the life of a declining field by accessing new or previously bypassed reservoirs.