The oil and gas industry is currently facing challenges due to low prices and environmentalists and globalists agendas. Small to medium companies in this sector need to optimize their resources and budgets to remain viable, especially those operating in areas with high water cuts, such as the Neuquén Basin in Argentina.
Billions of barrels of oil, valued at trillions of dollars, remain trapped underground in numerous mature fields globally. Data analytics techniques can help extract this resource at the lowest cost providing valuable insights from mostly underutilized data quickly.
Following the previous use cases (Part I, Predicting well openings (II), Scouting tool to evaluate Mendoza areas), this post will delve into the Content-Based Recommendation system included in a recently deployed cloud-based analytics solution implemented in the Google Cloud Platform for OILSTONE, an operator company in Neuquén Province, Argentina. The engine is powered by AI tools, relevant well features, and data extracted from publicly available official databases. Below is an image of the solution's front panel:
Similar to previous examples, this dashboard includes a map showing cumulative fluids productions, a table with relevant well features, dropdown filters for data segmentation, and various charts for visual and quantitative comparison of fluids productions and the number of wells by area. The solution might also include forecasting fluid production. The dashboard lets users quickly extract actionable insights and assess each area/reservoir with a few clicks.
The image above displays the Content-Based Recommendation Engine included in the analytics solution under consideration. It uses well features and data from the already mentioned official databases, to evaluate similarity and generate a Similarity Index (in %) for reservoir/field level comparisons.
The Borde Colorado Este reservoir, a very productive crude oil reservoir of the company, situated near Villa El Chocón in Neuquén Province, has also been the subject of extensive study. Recently, there has been an increase in the volume of water produced. Consequently, the company is seeking to address the issue and also identify alternative areas or reservoirs where it can allocate a budget to maintain its annual hydrocarbon production targets.
Now, the Recommendation Engine available is very useful in this scenario. As shown in the image below, when the user chooses "Yac. REFERENCIA" Borde Colorado Este from the drop-down menu and set, as an example, a conservative "Similarity Index" of 48%, the engine displays the top 4 out of 44 reservoirs, starting from the most similar one, DIVISADERO GENERAL SAN MARTÍN, to RANQUIL CO NORTE.
Choosing the highlighted reservoirs above from the "Yacimiento" drop-down in the solution's front panel can provide additional insight from the map, table, combo chart, etc., as depicted in the image below.
The decision-making team can immediately use the distilled list and data exported from the map and tables, and other insights gained, to further optimize the budget and take additional beneficial actions for the business, all of these with just a few clicks.
Insights like these are crucial for allocating resources, optimizing the operator's investment budget, and increasing profit. Would you like to learn more about our services and solutions? Contact us now!
DATAMATE/DataRobot, in partnership with Angel Solutions (SDG) and its trusted partners Geoloil Petrophysics and MineaOil Ltd, comprises highly trained professionals; and they are prepared and equipped with the best AI-powered platform and tools to effectively handle and provide solutions for your data project needs, regardless of type or volume.
Feel free to reach out to us directly or through our partners for prompt and reliable assistance.
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