Yet, harnessing this potential relies on various critical factors. This post delves into the world of tracer data and its collection, interpretation and presentation.
Despite being the sole technology offering irrefutable insights into the flow of movement, tracer data encounters its share of challenges. At times, it remains siloed and disconnected from broader reservoir datasets. How can we navigate these challenges to unlock the full potential of tracer technology and the invaluable insight it offers into the movement of fluid?
Reconciling Models with Data in The Energy Industry
Modelling plays a fundamental role in energy industry workflows. We are very much affected by the digital revolution we are living through, where concepts such as algorithms, models and data have become colloquial terms. Access to data is at the center point of this revolution, an observation that is certainly valid also when constructing models for energy industry applications.
The shape and composition of the underground are unknown, and any geometrical description at first is educated guesswork. For a model to be representative of reality, it must reconcile with actual measured data. When they accurately represent reality, models are valuable tools for predictions and scenario testing of technical solutions as well as business scenarios.
Fluid movement simulations used in the energy industry are, in essence, based on a few basic conservation laws. For example, equations for pressure (force per area) used in a reservoir simulator are based on the conservation of momentum, described by Newton’s 2nd law of motion. Combined with the conservation of fluid mass, this is used to calculate the movement of fluid in geological structures.
Models used to predict fluid movement also require a description of the overall geometry, behavior of fluids, rock properties, etc. Such information can be obtained from seismic studies, well-logging and physical sampling of rock and fluid.
Subsurface simulation efforts typically lead to an underdetermined system of equations where the number of unknowns far exceeds the number of equations. For this reason, any additional data is beneficial. Moreover, any new information complementary to the existing data will benefit a model more than small improvements on the information already available.
According to a scientific study based on the empirical data from the North Sea Snorre Field, chemical tracers present a valuable source of additional information on fluid movement in the reservoir. A tracer is a resilient chemical molecule that passively follows a specific phase as it flows into the subsurface. When unique tracers are introduced in all injectors, we can track fluid movement across all injector-producer paths in the subsurface d, providing a comprehensive map of fluid movement in the subsurface. At a fundamental level, each tracer introduces an additional conservation equation for the tracer mass. The addition of reservoir tracers, therefore, enables us to obtain relevant information that is directly related to the model. As the tracer signals are affected by the inter-well flow paths, the information provided is complementary to much of the information otherwise included in the models.
Stay tuned: our upcoming blog will discuss specific applications of tracer data in different industries.