How do you apply MRI to enhance reservoir simulation and forecasting?

1 Step 1: Acquire MRI data

The first step is to acquire MRI data from your reservoir. You can use either borehole or surface MRI methods, depending on your objectives, budget, and availability. Borehole MRI involves running a logging tool that emits radiofrequency pulses and records the response of the protons in the fluid and rock matrix. Surface MRI involves placing a large coil around the well or the reservoir and applying a similar technique. Both methods can provide high-resolution images of the reservoir properties and fluid distribution.

2 Step 2: Process and interpret MRI data

The next step is to process and interpret the MRI data to extract the relevant information for your reservoir simulation and forecasting. You need to apply various algorithms and corrections to the raw data, such as noise reduction, phase correction, inversion, and calibration. You also need to analyze the data in terms of relaxation times, which reflect the interaction of the protons with their surroundings. Relaxation times can be used to differentiate between different fluids and rock types, as well as to estimate porosity, permeability, and viscosity.

3 Step 3: Build a geological model

The third step is to build a geological model of your reservoir using the MRI data and other available data sources, such as core analysis, well logs, seismic, and production data. You need to integrate the data in a consistent and coherent way, using appropriate software and workflows. You need to define the reservoir geometry, structure, facies, and heterogeneity, as well as the fluid contacts, initial conditions, and boundary conditions.

4 Step 4: Generate a simulation grid

The fourth step is to generate a simulation grid that represents your geological model in a numerical form. You need to choose a suitable grid type, such as structured, unstructured, or hybrid, and a suitable grid resolution, depending on your computational resources and accuracy requirements. You need to map the MRI data and other reservoir properties onto the grid cells, using interpolation, upscaling, or downscaling techniques. You also need to ensure that the grid honors the well locations, faults, fractures, and other features.

5 Step 5: Run a reservoir simulation

The fifth step is to run a reservoir simulation using the simulation grid and a reservoir simulator software. You need to choose a suitable simulation model, such as black-oil, compositional, or thermal, and a suitable simulation method, such as finite difference, finite element, or streamline. You need to specify the production and injection scenarios, the fluid properties, the rock-fluid interactions, and the numerical parameters. You need to run the simulation and monitor the results, such as pressure, saturation, production rates, and recovery factors.

6 Step 6: Perform a forecast analysis

The final step is to perform a forecast analysis using the reservoir simulation results and the MRI data. You need to evaluate the performance of your reservoir under different scenarios, such as changing well rates, locations, or completions, or applying enhanced oil recovery techniques. You need to compare the simulation results with the MRI data to validate your model and identify any discrepancies or uncertainties. You also need to update your model and your forecast based on new data or information.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?