Video Accelerating Infrastructure-Led Exploration, Intelligently
Accelerate ILX with an intelligent solution that improves how data is acquired and how you use it.
Derisking near-field exploration using an accelerated workflow
Near-field exploration enables you to increase the output of oil and gas reservoirs using existing infrastructure to improve project economics and cycle times while lowering capex and carbon intensity. Our intelligent infrastructure-led exploration (ILX) workflow combines solutions across geology, petrophysics, and dynamic reservoir evaluation with advanced digital capabilities. With accelerated processing, interpretation, and contextualization, this connected and intelligent workflow enables you to derisk near-field reservoir evaluation within relevant operational time.
The intelligent ILX workflow quickly generates contextual wellbore and reservoir insights for faster decision making, no matter your objective: See deeper into your reservoir, confirm reserves sooner, expedite your completion strategy, or accelerate your field development plan and facilities design. Get the critical answers you need to maximize your asset performance—all while saving time and mitigating environmental impact vs. conventional near-field exploration workflows.
Our connected, intelligent ILX workflow leverages unprecedented digital capabilities to optimize asset performance with the maximum certainty possible. Using accelerated processing and interpretation, the prejob model is updated with geological and petrophysical data while tools are still in the well. Technologies such as the Quanta Geo™ photorealistic reservoir geology service acquire high-resolution wireline data. That geological contextualization is then combined with dynamic reservoir characterization results from the Ora™ intelligent wireline formation testing platform. This creates a calibrated wellbore model to extract key reservoir insights. Deep transient testing then derisks the 3D geocontexual model at deep scale to provide producibility metrics and prove commercial viability.