The New Subsurface Signals pillar seeks to transform our ability to characterize subsurface systems by developing new approaches to sense the subsurface and analyze multiple datasets, to identify critical system transitions, and to develop process control approaches. Each element will provide tools and methods (i.e., a toolbox) needed for success of other pillars as well as success of the SubTER grand challenge.
Research in the New Subsurface Signals Pillar is associated with four different topics, called elements, including:
- New Sensing Approaches
- Integration of Multi-Scale, Multi-Type Data
- Diagnostic Signatures and Critical Thresholds
- Adaptive Control Processes
New Sensing Approaches: The 10-year goal of this element is to enable adaptive control through identification of diagnostic signatures and critical thresholds by transformative collection and analysis of subsurface signals.
A wide variety of new sensors and techniques are available, but we will focus on approaches that promise to provide essential support for other SubTER pillars and elements. We also seek to leverage areas of rapid ongoing development, such as “big data” and photonics. We view New Sensing Approaches as a key cross-cutting component of the broader SubTER effort, providing the next-generation datasets required for monitoring subsurface processes. The objective is to characterize fracture distribution and behavior in situ as well as associated fluids flow and reactions with host rocks or other fluids. Development of both new sensors and time-lapse monitoring approaches are critical for meeting this objective. Advances in material science and manufacturing, especially nano-manufacturing, offer an exciting opportunity for development of next generation sensors that are cheap, small and high-performance.
A primary challenge in understanding subsurface fracture systems, whether natural or engineered, is understanding the geometry and spatial extent of the systems. This is particularly important away from the borehole where current methods possess poor resolution. Improved imaging of the fracture systems will provide essential information for the other pillars: wellbore, stress, and permeability.
Integration of Multi-Scale, Multi-Type Data: The overall 10-year goal for this effort is to advance integration of multi-scale and multi-type datasets to improve resolution and reduce uncertainty by joint analysis of multiple datasets in support of the broader NSS pillar.
A key need is the ability to derive robust estimates of subsurface fracture geometry, distribution and properties based on a mix of data types at a wide range of scales. The approach of this element incorporates advances in data mining, joint inversion and analysis. This element can be seen as a necessary step in the definition of diagnostic signatures and then in the control of processes. It is thus closely related to the last two elements of this pillar, but differs in that near-real time capabilities are not essential. The goal here is to improve understanding of the subsurface system at all scales and at all possible stages of operation: preparatory, during production or injection, during fracturing if any and in long-term monitoring. This effort also seeks to advance implementation of emerging data computer science capabilities within the geoscience domain to support efficient, multi-scale, multi-data type analyses for geosystems related needs. Special attention will focus on the control of data quality and to the monitoring infrastructure (confidence in sensor behavior, for example).
Diagnostic Signatures and Critical Thresholds: Fracture development and propagation are highly nonlinear systems that often display dramatic transitions in system behavior. Identifying diagnostic signatures of these critical thresholds would be highly useful in understanding and predicting the behavior of these systems. Examples of critical transitions relevant to sustainable energy production and waste storage include the breaching of carbon sequestration caprock, the connection of hydraulically-induced fractures with an existing fault, wellbore integrity failures, or the influence of abrupt precipitation and dissolution processes on fluid flow. The nonlinear behavior makes purely deterministic modeling difficult, as small variations in pre-existing conditions may greatly affect the evolution of the entire system. Knowledge of integrated diagnostic signatures could pave the way for research focused on identifying precursors leading to critical transformations and the development of new sensor suites optimized for early detection of such thresholds. Using laboratory and field data collected during abrupt transitions in subsurface system behavior, physics-based as well as complexity-based (e.g., graph theory, pattern and fuzzy) approaches could be advanced to identify diagnostic signatures of critical system transitions using multiple datasets.
Adaptive Control Processes: The 10-year goal of this element is to enable autonomous data collection, management, reduction, integration, and visualization, integrated with THMC-G models, parallel computing, and cloud service architecture.
The development of autonomous acquisition, processes and assimilation approaches is critical for adaptive control of subsurface systems. Research associated with advancing autonomous analytics blends systems engineering with computational and subsurface expertise. New acquisition software will be needed to autonomously trigger and co-acquire data from multiple sensors and to stream those datasets to computational centers. There is a need for data collection, management, processing and visualization workflows and tools that can handle large and heterogeneous datasets and perform real-time quality control steps in a manner performed today by subsurface scientists. Inversion approaches, such as those described above, could be automated to allow estimation of key parameters or states using the acquired field datasets. Approaches to assimilate direct measurements and inversion results into THMC models will be needed to guide “adaptive control” of subsurface fractures, flow and reactions.