Tutorial: Organic Mudstone Petrophysics, Part 2: Workflow to Estimate Storage Capacity
- Kent Newsham (Occidental Petroleum Corp.) | Joe Comisky (Devon Energy Corporation) | Roland Chemali (Occidental Petroleum Corp.)
- Document ID
- Society of Petrophysicists and Well-Log Analysts
- Publication Date
- April 2019
- Document Type
- Journal Paper
- 181 - 207
- 2019. Society of Petrophysicists & Well Log Analysts
- 9 in the last 30 days
- 288 since 2007
- Show more detail
This is the second of a three-part tutorial describing a workflow for evaluating unconventional resources including organic mudstones and tight siltstones. Part 1 reviewed the unique challenges and provided an overview of the proposed workflow (Newsham et al., 2019). Part 2 describes in detail the many components of the workflow and how they come together to determine the storage capacity of the reservoir. Part 3 links the petrophysical results to the production potential in terms of fractional flow and water cut and will present alternate cross-checks of the storage properties to validate the results.
As stated in Part 1, one of the most important functions that the petrophysicist provides is the estimation of accurate storage properties. However, when the authors survey the range of workflows used to estimate the storage capacity of these complex systems, we find a wide range of options. Solutions can vary from simple deterministic to more complex probabilistic approaches. Whatever the method, the objective should be the same: to provide consistent, portable hence reliable estimation of hydrocarbon storage capacity, also known as “Petrophysics CPR.” As mentioned in Part 1, estimation of hydrocarbon storage is more than just the calculation of porosity and water saturation. In this tutorial, we will describe a workflow that has been successfully used to evaluate thousands of wells in the Permian Basin with great consistency. The authors have nearly 100 wells with core data to calibrate the workflow. We will show examples of the workflow’s portability by highlighting examples from the Midland Basin, the Texas Delaware Basin and the New Mexico Delaware Basin. We will show how every property measured in core matches to log-based profiles using a combination of deterministic and the constrained simultaneous solution methods. The workflow also is found to be reliable in other basins throughout the world, however, the examples will be confined to the Permian Basins.
|File Size||28 MB||Number of Pages||28|