R&D;data Engineer

Responsibilities
Qualification:
• PhD in Data Science and petroleum Engineering.
• Skilled researcher with extensive experience in applied mathematics and computational science, with emphasis on uncertainty quantification and dealing with huge database.
• Able to adapt, improve, and develop new approaches that serve studying and simulating algorithm.
• Experience in projects from conception to completion.
• Able to learn and comprehend new systems and methods quickly, set and achieve goals and work well under pressure.
• Ability to work well independently, as member of a team, and relate easily with all kinds of people.
• Proficient in Software: Python, MATLAB, Mathematica, LATEX, C , ICDL Microsoft office
• Operating System Microsoft Windows.
Qualifications
Responsibilities:
• Data Mining (Analyze and Classify Data / Dashboards / Witsml). Description. - Create visualization dashboards, combining relevant data from daily drilling report system, WITSML data source and any other data source available (i.e. geological and geo-mechanic models). This is to have the ability to classify events details and causes, as well as identify additional parameters available that might be useful to include.
• Existing WFT Model Manual Calibration. Description. - The existing model will be fine-tuned using at least 40 wells with specific events from one area of study. For this task, CENTRO Monitoring software will be used. All the actions will be captured and mapped in a process for automation using AI techniques.
• Blind Test of Calibrated Model. Description. - Once the previous task is finished, the model will be validated using at least 5 more wells of the area. Results will be documented and determine next steps based on success criteria achievement.
• Analyze and identify pre-event patterns. Description. - This task will run in parallel to the previous two tasks. The goal is to identify and include additional data driven parameters that are not part of the original methodology and might have strong influence in these stuck pipe events.
• Development of AI model. Description. - An automation algorithm will be developed to train and calibrate the existing event detection methodology on different operation areas. The artificial intelligence technique to be used will be determined based on the nature of the procedure, the data itself, use case requirements and existing industry literature. It will also include an additional layer of parameters based on patterns discovered in the previous task.
• Testing of Overall Solution. Description. - Test the overall solution using the data of a 2nd area. Train the model with 40 wells and use it on 5 additional wells to blind test the same. Use the same period to stabilize the model and fine tune it.
• Wrap up model. Description. - Develop an integration layer to be able to connect the plugin with real time engineering systems and applications. Delivering the final code

https://www.naukrigulf.com/r-d-data-engineer-jobs-in-dammam-khobar-eastern-province-saudi-arabia-in-weatherford-international-oil-field-services-4-to-5-years-n-cd-10000017-jid-070521500148