Oilfield operations capture large amounts of raw data, and make it available through real-time databases or historians. During the last decade, most large oil companies have made significant investments to enable such data capture. Simultaneously, data analytics, in particular within machine learning and mathematical optimization, has experienced much success in many sectors. However, the oil and gas industry has not been able to keep pace with these fast growing, high potential technologies. Thus, stored operational data is by no means utilized for production enhancement according to its potential. This is especially true for daily production optimization, which often consists of manual and work-intensive processes. Solution Seeker’s ProductionCompass AI, provides a solution to this challenge through its innovative data compression and analytics algorithms, its Compact Database technology, and its innovative visualization capabilities.
Stored operational data is by no means utilized for production enhancement according to its potential.
The first step of Solution Seeker’s data processing pipeline is to automatically and continuously mine all raw production data from thousands of sensors, using machine learning techniques and advanced statistical analysis to filter, sort, clean, squash and prepare information sets for the AI engine. The processed production data is stored in our proprietary compressed Compact Database in real-time, retaining operation-relevant information at less then 1% of the initial data volume. The machine learning algorithms that constitute the core of the AI engine, then run on this improved and compressed dataset, removing a significant hurdle often overlooked in oil and gas big-data discussions; low quality datasets.
The "everything is information" paradigm.
Currently it is common for engineers to visually inspect data, with analysis being limited to time spans where information is known to be rich and relevant (such as during well test campaigns). This is only natural, since manual data inspection is such a time consuming task. The reason is that it is challenging to manually select the time spans which are most important to analyze. This is especially true for fields without a dedicated test separator, like subsea tie-in fields. The downside is that large quantities of data lies untouched. However, with a constant stream of refined and processed data, our Compact Database enables an "everything is information" paradigm, which leads to a much higher level of data utilization. Thus, even before introducing advanced analytics and optimization algorithms, ProductionCompass AI ensures that the constant stream of refined and processed data holds value on its own.