Production & Stimulation Engineering
The production engineering expertise provided by Fenix is focused on hydraulic fracturing and all connected engineering involved; e.g. NPV investment optimization, well planning, completion requirements, lower completion selection, frac design & execution, well test planning, data room exercises, production analysis and production forecasting.
Instead of focusing on a specific aspect of the stimulation process, we look at the big picture of treatment optimization at the start of the design, from the reservoir understanding up. This ensures that we solve the right problem, taking into account all data available. In line with this we have developed, populated and analyzed several production databases for customers.
For all services we adopt the philosophy that the expertise of the engineer is more important than the tools used. We also believe that a presence in the complete cycle; planning, execution and evaluation is creating the most value. We support our clients during each of the above steps.
Our stimulation and hydraulic fracturing engineering is driven by available data. Before drilling a well, the data will be limited to the reservoir description and assumptions included in the initial static model developed from geology and geophysics information. Additional data usually becomes available in a later phase from logging, coring, and production- and/or injection testing to obtain permeability information. Depending on the type of reservoir the exact workflow can be different, but the final aim is always to maximize productivity within the project’s economic constraints.
Our engineering expertise supports the entire well stimulation process from candidate selection to post-stimulation performance evaluation. We provide a broad range of hydraulic fracture engineering services, supporting clients with fracture design, completion selection, setting up the ITT to make sure that the right questions are asked, analyzing different tenders to make a valid comparison based on technical and operational equivalent assumptions and to better predict the most likely actual cost with the different propositions, detailed treatment optimization, on-site engineering and supervision (fluid QA/QC, mini-frac analysis, etc.), welltest program input/requirements and welltest/production data analysis.