Jobloria
Geophysicist / Rock Physicist
Great Lakes Truck Driving School
Location : Houston, TX, 77002
Job Type : Full Time
Date Posted : 2 December 2025
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Geophysicist / Rock Physicist (R&D) - AI/ML Quantitative Interpretation
Houston, TX, US, 77032
We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world’s largest providers of products and services to the global energy industry.
Job Duties
- Seismic Inversion (acoustic (poststack) and elastic (prestack AVO/AVA based) & Integration with Petrophysical / Rock Physics Analysis:
- Perform rock physics analysis to model Elastic Impedance and Extended Elastic Impedance parameters in relation with reservoir properties such as porosity, Vsh, and saturation.
- Develop and apply advanced seismic inversion techniques to derive rock property models.
- Integrate seismic images with well logs and core data to generate 3D geologic static reservoir models using geostatistical and sequence stratigraphy principles.
AI / ML Implementation:
- Design and implement AI and ML algorithms (using Python) to automate and enhance the interpretation of seismic data.
- Develop predictive models to estimate rock properties and reservoir parameters with associated uncertainties.
- Use AI-driven quantitative interpretation methods to improve seismic-to-petrophysical property mapping and reservoir characterization.
Uncertainty Quantification of Reservoir Characterization
- Analyze and quantify the uncertainty of the 3D distribution of rock properties and fluid saturations using combination of AI models and mathematical statistics in the solving the inverse problem.
- Validate reservoir and ML models against known well data (blind tests) and adjust for consistency in the context of sequence stratigraphy and seismic facies. Analyze generalization gap and quantify epistemic and aleatoric uncertainty.
Collaboration and Innovation:
- Collaborate with multi-disciplinary teams including geologists, reservoir engineers, and data scientists to refine models and enhance predictions.
- Stay up to date with the latest advancements in AI, DL, and geophysics to innovate new techniques and improve workflows
- Contribute to R&D publications, presentations, and patents related to rock physics, seismic inversion, AI, and quantitative reservoir characterization.
Qualifications
- Skills acquired through the completion of an undergraduate degree in Science or Engineering.
- 10 years of related experience.
- Completion of a masters or PHD in Science or Engineering is preferred.
Candidates with qualifications exceeding the minimum job requirements will be considered for higher-level positions based on their experience, additional job requirements, and current business needs. Depending on their education, experience, and skill level, candidates may be eligible for a range of job opportunities, including positions ranging from Senior Scientist Technical Advisor, Principal Scientist Technical Advisor and Chief Scientist Technical Advisor.
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Location
3000 N Sam Houston Pkwy E, Houston, Texas, 77032, United States
Job Details
Requisition Number:203952Experience Level:Experienced HireJob Family:Engineering/Science/TechnologyProduct Service Line:Landmark Software & ServicesFull Time / Part Time:Full Time
Additional Locations for this position:
Compensation Information
Compensation is competitive and commensurate with experience.
Nearest Major Market:HoustonJob Segment:Quantitative Analyst, Data
Freqently Asked Questions
Professionals in Houston integrate seismic inversion results with well logs and core data to create detailed 3D geologic reservoir models. This approach combines geostatistics and sequence stratigraphy, enabling precise mapping of rock properties like porosity and fluid saturations, crucial in energy sector projects.
Advanced AI/ML methods, including Python-based predictive modeling, automate seismic data interpretation. These techniques improve seismic-to-petrophysical property mapping by quantifying uncertainties and enhancing reservoir parameter estimations, thus boosting accuracy in quantitative interpretation workflows.
Starting as a technical expert, one can advance to senior scientist or principal advisor roles by deepening expertise in seismic inversion and AI-driven reservoir modeling. Leadership in R&D and cross-disciplinary collaboration often leads to chief scientist positions, reflecting growth in responsibility and innovation influence.
Houston's complex subsurface geology demands high precision in integrating seismic and petrophysical data. Local reservoir heterogeneity and extensive well log availability require tailored inversion techniques and AI models that address regional geological variability and improve reservoir characterization accuracy.
Houston, as a global energy hub, maintains strong demand for seasoned geophysicists skilled in seismic inversion and AI applications. Competitive hiring reflects ongoing investments in reservoir characterization, making it a fertile ground for professionals with advanced quantitative interpretation expertise.
This role uniquely blends R&D in seismic inversion with AI-driven quantitative interpretation within a company primarily known for training drivers. It offers geophysicists an innovative environment to apply rock physics and machine learning in energy-related product development and reservoir analysis.
The company fosters a culture of innovation and career growth, investing in employee development. Geophysicists benefit from interdisciplinary collaboration and cutting-edge AI/ML tools, positioning them to contribute to impactful research and patentable advancements in seismic and rock physics interpretation.
Experienced geophysicists in Houston typically earn between $110,000 and $150,000 annually, depending on expertise in advanced seismic inversion and AI modeling. Competitive compensation aligns with the city’s status as an energy industry nexus and the specialized skill set required.
While a master’s or PhD is preferred, credentials like Professional Geoscientist (PG) licensure and specialized AI/ML certifications can boost employability. Local employers value advanced education paired with practical experience in seismic data analysis and quantitative reservoir characterization.
By combining AI algorithms with statistical methods, uncertainty quantification assesses confidence in 3D rock and fluid property distributions. This approach refines reservoir simulations, allowing more reliable predictions and risk assessments tailored to Houston’s complex geological settings.