Brunel
Job Summary:
The Geological Technician / Data Scientist
supports the SSOP Operations Geology team by integrating geological expertise with advanced data analytics to enhance subsurface understanding and operational efficiency. This hybrid role involves managing and interpreting geological data, creating visualizations, supporting operations geology, and applying data science techniques to optimize exploration and development workflows. Responsibilities
Geological Support
Compile, organize, and analyze geological and geophysical data from wells, cores, and seismic surveys Support well planning activities by generating geological displays using software such as Petrel, ArcGIS, and Gravitas Maintain and update geological databases and document repositories Perform quality control on incoming geological data to ensure consistency and accuracy Assist in analyzing geological data and preparing reports for internal stakeholders Data Science & Analytics
Analyze subsurface datasets (e.g., well logs, seismic, core, production) using statistical and machine learning techniques Clean, process, and manage large structured and unstructured datasets Build and deploy machine learning models for pattern recognition, anomaly detection, and clustering of geological features Create interactive dashboards and visualizations to communicate insights to technical and non-technical audiences Support digital transformation initiatives by automating workflows and improving data accessibility Stay current with emerging technologies in geoscience and data analytics Qualifications
Bachelor’s or Master’s degree in Geology, Geophysics, Petroleum Engineering, Data Science, or related discipline. 2 years of experience in geological, geophysical, or geotechnical support and/or subsurface data analytics. Proficiency in geological software (e.g., Petrel, Kingdom, Techlog) and data analysis/visualization platforms (e.g., Python, Power BI). Strong programming skills in Python, R, or similar languages. Strong organizational, analytical, and communication skills. Ability to work independently and collaboratively in multidisciplinary teams. Preferred Skills
Experience with well log interpretation and core analysis Knowledge of reservoir characterization and petrophysics Familiarity with drilling operations and wellsite geology Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) Familiarity with oilfield data formats (e.g., WITSML, LAS, SEG-Y) Familiarity with cloud computing and data storage solutions (e.g., Azure, AWS) Ability to work in agile, cross-functional environments
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supports the SSOP Operations Geology team by integrating geological expertise with advanced data analytics to enhance subsurface understanding and operational efficiency. This hybrid role involves managing and interpreting geological data, creating visualizations, supporting operations geology, and applying data science techniques to optimize exploration and development workflows. Responsibilities
Geological Support
Compile, organize, and analyze geological and geophysical data from wells, cores, and seismic surveys Support well planning activities by generating geological displays using software such as Petrel, ArcGIS, and Gravitas Maintain and update geological databases and document repositories Perform quality control on incoming geological data to ensure consistency and accuracy Assist in analyzing geological data and preparing reports for internal stakeholders Data Science & Analytics
Analyze subsurface datasets (e.g., well logs, seismic, core, production) using statistical and machine learning techniques Clean, process, and manage large structured and unstructured datasets Build and deploy machine learning models for pattern recognition, anomaly detection, and clustering of geological features Create interactive dashboards and visualizations to communicate insights to technical and non-technical audiences Support digital transformation initiatives by automating workflows and improving data accessibility Stay current with emerging technologies in geoscience and data analytics Qualifications
Bachelor’s or Master’s degree in Geology, Geophysics, Petroleum Engineering, Data Science, or related discipline. 2 years of experience in geological, geophysical, or geotechnical support and/or subsurface data analytics. Proficiency in geological software (e.g., Petrel, Kingdom, Techlog) and data analysis/visualization platforms (e.g., Python, Power BI). Strong programming skills in Python, R, or similar languages. Strong organizational, analytical, and communication skills. Ability to work independently and collaboratively in multidisciplinary teams. Preferred Skills
Experience with well log interpretation and core analysis Knowledge of reservoir characterization and petrophysics Familiarity with drilling operations and wellsite geology Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) Familiarity with oilfield data formats (e.g., WITSML, LAS, SEG-Y) Familiarity with cloud computing and data storage solutions (e.g., Azure, AWS) Ability to work in agile, cross-functional environments
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