Frac operations are rich with potentially valuable data. However, integrating it and using it to improve performance and squeeze more efficiency and cost out of already optimized operations can be challenging.
Understanding the opportunity and collaborating across service providers to realize the value of the data is a big, and often expensive challenge. Enthought scientists’ oilfield domain expertise, analytical software development and infrastructure skills, covering all data types, enable collaboration to efficiently identify the opportunity and develop the right software technology to utilize it.
Completions engineers know analogue wells, stages, service companies, and often even supervisors where they had the best performance. However, exploring the 1,000’s of legacy stages, validating the data, integrated viewing, and finally getting it in front of the people running the operation (where the value is), is near impossible. This is where Enthought can help. Our sweet spot is getting value from large and complex data, removing drudgery from experts who have to deal with them.
Thousands of offset well stages provide a unique opportunity to benchmark performance by multiple factors, initially identifying similar formation types, then apply machine learning techniques to recommend completion pumping programs, and then visualize real-time data with ideal performance during operations.
Pumping schedules, including pressure ramp-up, stabilized rate values, and chemical additives schedules and timings offer a unique opportunity to squeeze costs out of completions. Identifying and visualizing best performer offsets, using these in pre-completion team meetings, and having them available with supervisors during wellsite operations provides greater insights and enables better decisions. Here, a graph shows ideal performance with a window of uncertainty determined by offset stage performance. Service company and supervisor variances can be the most significant factors.
Basin development can often benefit from a specifically designed field experiments in key wells, including offsets with distributed and seismic measurements. Learnings from these projects can offer significant benefits in subsequent basin development through increased recovery, more efficient completion operations, or both, but are challenged by data integration, visualization and analysis.
Enthought scientists collaborate with you to develop software that integrates disparate data sets from multiple service providers, applying AI/machine learning techniques, including in real-time, to conduct field experiments so that targeted knowledge is gained, value quantified, and implementable plans can be developed for subsequent development.
Enthought geoscientists’ understanding of the subsurface and experience with all data types enables collaboration to design experiments to optimize nearby basin development, well and completion designs, scaling to maximize recovery.
Custom tools were built to show DAS/DTS (Distributed Acoustic and Temperature Sensing) and data from surface seismic nodes in context with real time rate and pressure data from multiple frac trucks. Automated ingestion tools were created to process data from 3 different service companies, store in a data lake and provide real time visualization to the field and HQ.
Well trajectories are visualized along with the located microseismic events. Microseismic event location takes some processing time. These events are integrated into the system automatically when processed, and shown in relation to well bores to facilitate real time decisions.
Your engineering and operational experts collaborating with Enthought domain, data and scientific software development scientists can scope potential pilot projects, work to quantify value, and decide if there are opportunities in your play.