Why ALS’ Remote Operations Center?
The Remote Operations Center is where your captured downhole data is integrated, painting a clear and objective picture of the potential of your wellbore.
From Advanced Geoscience Analysis and Mass Spectrometry, to Geosteering and Quality Control, all of our functions are in one location, working for you.
The result? Unparalleled coordinaton and collaboration that delivers cost savings and the potential for increased production.
Geological experts monitoring all data in real-time. This is another investment ALS Surface Logging makes towards providing accurate data, a quality product and reassurance to its customers.
Our Quality Control team members work 24/7 and are regional experts in the areas where ALS Surface Logging is working. We are obligated to provide excellence in the service that is our speciality, underlining our commitment to our customers.
Data Management & Integration
Our Remote Operations Center offers a data management service, headed by experienced geologists who will gather, check, distribute, and archive all data from the rig.
This allows the client to have single source accountability for all wellsite data. At the completion of the project, the service will deliver organized digital and hard copies of the well data to the client and any specified other bodies.
The data management service will also work with BSEE or other governing bodies to ensure proper reporting and documentation is completed correctly and on time.
Remote Pore Pressure Monitoring
ALS Surface Logging offers on-site, in house, and 24/7 remote pore pressure monitoring. On-site pore pressure monitoring is done via DynaView Software. This allows for the
on-site geologist to also correlate offset wells, plot formations in 3 dimensional horizon layers, and account for wellbore collision in highly developed areas.
In addition to Dynaview, the remote and in house pore pressure monitoring specialists also utilize DUG Insight to allow for the interpretation of seismic data for pre-well planning, and monte-carlo simulations to account for potential errors in observed data.