Like many oiflield operators in the Gulf of Mexico, Oxy has dedicated teams responsible for producing energy efficiently and reliably. One of the concerns of that team related to asphaltene management. In collaboration with MicroSilicon, a review of a few of their GOM oils established that, as had been previously seen in the Middle East, the paramagnetic signature consistently correlated with asphaltene content. This gave confidence to use the signature as a potential input for offshore production decisions and in 2022 a Quantum RF Asphaltene Analyzer ("QRF") was deployed onto the Marco Polo platform.

One new challenge for the offshore analysis, however, was that multiple wells on the seabed were commingled to two risers coming to the surface and the asphaltene sensor was plumbed to only one of those risers. To meet this challenge, it proved very beneficial to be able to integrate the asphaltene data with other real-time data traditionally available to the operator, such as well alignments. The integrated results were then viewable on a dashboard configured to that vendors requirements as well as on the operator’s SEEQ dashboard.

Communication with SEEQ was configured to be bidirectional and routed through Google BigQuery. On the MicroSilicon side, our software was able to access dedicated html port to parse SEEQ format which was then converted to our internal database structure and stored on BigQuery, and on the SEEQ side a dedicated connector was given read access to a secure table containing real-time updates of data from the Quantum RF. All bidirectly communication is fully encrypted with no exposed client information. One operator accessing MicroSilicon data via SEEQ does not have any visibility to what other operators might also be using SEEQ. Similarly, MicroSilicon can only read that data which the client has chosen to expose on their SEEQ html portal.

An example of the integrated configuration is shown below. The top two tracks are data from the seabed, with notification of which well is producing and then a track of wellhead temperatures which serves a proxy for downhole flow rate. The subsequent tracks contain a mix of client and MicroSilicon data, including Vpp (for asphaltene percentage), Q (for water cut) and Frequency (for gas/oil ratio).

In this particular example, the operator was also taking periodic samples and having them analyzed by SARA and they requested that we display the asphaltene ratio from SARA alongside the Vpp data determined from the QRF

A second issue arose because they had one system but were producing up two risers. In collaboration with the operator, we arranged our sampling skid to have two separate inputs, one for the "A" riser and one for the "B". Each input had a small separator. The QRF then alternatively sampled from those separators, so that while one separator was filling the oil from the other separator was being analyzed. The data then passed to BigQuery a "Vpp_A" and "Vpp_B", etc, so that the dashboard can identify the separate streams. In this way, no information was lost (e.g. if a troublesome asphaltene was flowing up one riser, but not the other).