Job Details

Job Duties

We are seeking a highly skilled and innovative Geophysicist   with a strong background in GenAI / Deep Learning and Python coding  for Seismic Imaging / Full Waveform Inversion and Quantitative Interpretation. The successful candidate will focus on integrating seismic imaging and inversion with petrophysical analysis, sequence stratigraphy, and seismic facies ML classification to build high-resolution 3D reservoir models. This role involves using cutting-edge machine learning and deep learning techniques to estimate uncertainty in the distribution of key rock properties, such as porosity, volume of shale (Vsh), and saturation in oil and gas reservoirs.

• Seismic Inversion (elastic FWI of shot gathers and acoustic (poststack) and elastic (prestack AVO/AVA based) & Integration with Petrophysical / Rock Physics Analysis:.
• 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

• PhD  in Geophysics, Rock Physics, Petroleum Engineering, or a related field.

Technical Skills:

• Strong proficiency in **Python** programming and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with seismic inversion techniques and seismic interpretation software.
• Solid understanding of petrophysical and rock physics principles and methods.
• Knowledge of sequence stratigraphy, seismic facies analysis, and their role in reservoir modeling.

Experience:

• Minimum of 3-5 years of experience in quantitative interpretation, reservoir modeling, and petrophysics / rock physics.
• Proven track record of using AI/ML in subsurface modeling or related fields is a strong plus.

Soft Skills:

• Strong analytical thinking and problem-solving skills.
• Excellent communication and ability to work in a collaborative, multi-disciplinary R&D environment.

Preferred Qualifications:

• Experience in the oil and gas industry, in particular in the field of subsurface uncertainty quantification.
• Familiarity with cloud-based computational platforms for running large-scale AI models.
• Previous R&D or publication experience related to AI/DL applications in geophysics.

Consideration For Higher Level Role:

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Principal Technical Professional Technologist or Technical Advisor Scientist.

Job Duties

We are seeking a highly skilled and innovative Geophysicist   with a strong background in GenAI / Deep Learning and Python coding  for Seismic Imaging / Full Waveform Inversion and Quantitative Interpretation. The successful candidate will focus on integrating seismic imaging and inversion with petrophysical analysis, sequence stratigraphy, and seismic facies ML classification to build high-resolution 3D reservoir models. This role involves using cutting-edge machine learning and deep learning techniques to estimate uncertainty in the distribution of key rock properties, such as porosity, volume of shale (Vsh), and saturation in oil and gas reservoirs.

• Seismic Inversion (elastic FWI of shot gathers and acoustic (poststack) and elastic (prestack AVO/AVA based) & Integration with Petrophysical / Rock Physics Analysis:.
• 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

• PhD  in Geophysics, Rock Physics, Petroleum Engineering, or a related field.

Technical Skills:

• Strong proficiency in **Python** programming and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with seismic inversion techniques and seismic interpretation software.
• Solid understanding of petrophysical and rock physics principles and methods.
• Knowledge of sequence stratigraphy, seismic facies analysis, and their role in reservoir modeling.

Experience:

• Minimum of 3-5 years of experience in quantitative interpretation, reservoir modeling, and petrophysics / rock physics.
• Proven track record of using AI/ML in subsurface modeling or related fields is a strong plus.

Soft Skills:

• Strong analytical thinking and problem-solving skills.
• Excellent communication and ability to work in a collaborative, multi-disciplinary R&D environment.

Preferred Qualifications:

• Experience in the oil and gas industry, in particular in the field of subsurface uncertainty quantification.
• Familiarity with cloud-based computational platforms for running large-scale AI models.
• Previous R&D or publication experience related to AI/DL applications in geophysics.

Consideration For Higher Level Role:

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Principal Technical Professional Technologist or Technical Advisor Scientist.

Job Duties

We are seeking a highly skilled and innovative Geophysicist   with a strong background in GenAI / Deep Learning and Python coding  for Seismic Imaging / Full Waveform Inversion and Quantitative Interpretation. The successful candidate will focus on integrating seismic imaging and inversion with petrophysical analysis, sequence stratigraphy, and seismic facies ML classification to build high-resolution 3D reservoir models. This role involves using cutting-edge machine learning and deep learning techniques to estimate uncertainty in the distribution of key rock properties, such as porosity, volume of shale (Vsh), and saturation in oil and gas reservoirs.

• Seismic Inversion (elastic FWI of shot gathers and acoustic (poststack) and elastic (prestack AVO/AVA based) & Integration with Petrophysical / Rock Physics Analysis:.
• 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

• PhD  in Geophysics, Rock Physics, Petroleum Engineering, or a related field.

Technical Skills:

• Strong proficiency in **Python** programming and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with seismic inversion techniques and seismic interpretation software.
• Solid understanding of petrophysical and rock physics principles and methods.
• Knowledge of sequence stratigraphy, seismic facies analysis, and their role in reservoir modeling.

Experience:

• Minimum of 3-5 years of experience in quantitative interpretation, reservoir modeling, and petrophysics / rock physics.
• Proven track record of using AI/ML in subsurface modeling or related fields is a strong plus.

Soft Skills:

• Strong analytical thinking and problem-solving skills.
• Excellent communication and ability to work in a collaborative, multi-disciplinary R&D environment.

Preferred Qualifications:

• Experience in the oil and gas industry, in particular in the field of subsurface uncertainty quantification.
• Familiarity with cloud-based computational platforms for running large-scale AI models.
• Previous R&D or publication experience related to AI/DL applications in geophysics.

Consideration For Higher Level Role:

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Principal Technical Professional Technologist or Technical Advisor Scientist.

Job Duties

We are seeking a highly skilled and innovative Geophysicist   with a strong background in GenAI / Deep Learning and Python coding  for Seismic Imaging / Full Waveform Inversion and Quantitative Interpretation. The successful candidate will focus on integrating seismic imaging and inversion with petrophysical analysis, sequence stratigraphy, and seismic facies ML classification to build high-resolution 3D reservoir models. This role involves using cutting-edge machine learning and deep learning techniques to estimate uncertainty in the distribution of key rock properties, such as porosity, volume of shale (Vsh), and saturation in oil and gas reservoirs.

• Seismic Inversion (elastic FWI of shot gathers and acoustic (poststack) and elastic (prestack AVO/AVA based) & Integration with Petrophysical / Rock Physics Analysis:.
• 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

• PhD  in Geophysics, Rock Physics, Petroleum Engineering, or a related field.

Technical Skills:

• Strong proficiency in **Python** programming and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with seismic inversion techniques and seismic interpretation software.
• Solid understanding of petrophysical and rock physics principles and methods.
• Knowledge of sequence stratigraphy, seismic facies analysis, and their role in reservoir modeling.

Experience:

• Minimum of 3-5 years of experience in quantitative interpretation, reservoir modeling, and petrophysics / rock physics.
• Proven track record of using AI/ML in subsurface modeling or related fields is a strong plus.

Soft Skills:

• Strong analytical thinking and problem-solving skills.
• Excellent communication and ability to work in a collaborative, multi-disciplinary R&D environment.

Preferred Qualifications:

• Experience in the oil and gas industry, in particular in the field of subsurface uncertainty quantification.
• Familiarity with cloud-based computational platforms for running large-scale AI models.
• Previous R&D or publication experience related to AI/DL applications in geophysics.

Consideration For Higher Level Role:

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.  Depending on education, experience, and skill level, a variety of job opportunities might be available including Principal Technical Professional Technologist or Technical Advisor Scientist.