Production Engineers have relied on physics based analysis to optimize artificial lift to great effect for decades. For sucker rod pump in particular, dynamometer analysis is at the core of optimization efforts, allowing engineers to visualize and interpret downhole and surface conditions. Technologies enabling remote visibility, remote analysis, and logic-based control of fillage have allowed dynamometer analysis to create the foundation for a ‘pump-by-exception’ operating model. However, these innovations were built on legacy data transmission, hardware, and software architectures, which created high-cost, low-quality data with dated and clunky user interactions. Ambyint is built with modern technology best practices across our platform. This creates high quality, event-based data, a clean well analysis user interface, and workflow tools available in either a web browser or mobile device to allow the field and office to be in sync with the wells and one other at all times.
Ambyint is built on the foundation of using better math and higher quality data resolution to overcome some of the assumptions and limitations of traditional dynamometer card analysis. Ambyint has taken production optimization several steps forward with our adaptive control, artificial intelligence, and machine learning capabilities.
Oilfield production optimization software is outdated. The days of multiple clicks, several sub-menus, and visualizations that do not automatically adjust to the screen size are eliminated with Ambyint. Our platform marries robust analysis tools with the same design best practices of modern consumer software.
By digitizing the visual input from millions of dynocards, Ambyint’s AI platform is able to perform micro pattern analysis to diagnose downhole and surface anomalies and optimize well parameters.