Job Detail

Job Details

Description

HKN Energy Ltd. is a privately held, independent energy company with oil exploration and production operations in the Kurdistan Region of Iraq (KRI).

HKN Energy is located in the prolific Zagros fold and thrust belt of Northern Kurdistan. We have a highly experienced, diverse team with work experience in over 80 different countries. HKN Energy is committed to building a company culture that is guided by its Core Values of Integrity, Respect, Excellence, Teamwork and Commitment.

Description:  We are seeking a highly skilled and motivated Data Scientist to join our Reservoir and Production Technology team. The ideal candidate will work at the intersection of data science, reservoir engineering, and production operations, leveraging advanced analytics, machine learning, and statistical modeling to optimize hydrocarbon recovery, production efficiency, and field development strategies.

This role is crucial in driving data-driven decision-making by integrating subsurface data (logs, core, seismic), production data (rates, pressures, downtime), and surface facility data (flowlines, choke settings, sensors).

Objectives and Deliverables will include:

• Develop predictive models for reservoir performance forecasting, decline curve analysis, and production optimization.
• Apply machine learning algorithms (e.g., random forests, gradient boosting, time series models, deep learning) to identify patterns in production and well performance data.
• Integrate diverse datasets (PVT, SCADA, seismic, well logs, simulation outputs) to create actionable insights for reservoir management.
• Collaborate with reservoir engineers, geologists, and petroleum engineers to design data-enabled workflows.
• Support real-time data analytics and build dashboards for operational surveillance and anomaly detection.
• Participate in digital transformation initiatives and help implement AI/ML tools in the field and corporate settings.
• Ensure data quality, cleaning, normalization, and management of large datasets using appropriate data engineering tools.
• Provide statistical insights during field development planning, well intervention analysis, and history matching support.
• Stay attuned to industry trends and new technologies in petroleum data science and reservoir digitalization.