MCI logging for processing downhole measurements
US-10301935-B2 · May 28, 2019 · US
US12265196B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12265196-B2 |
| Application number | US-202217977994-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 31, 2022 |
| Priority date | Oct 31, 2022 |
| Publication date | Apr 1, 2025 |
| Grant date | Apr 1, 2025 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A method and system for correlating two or more logs. The method may include reviewing an openhole log to identify one or more depths within a wellbore for testing, disposing a fluid sampling tool into the wellbore, creating a correlation log with the fluid sampling tool, depth-matching the correlation log to the openhole log to create a relative shift table, and moving the fluid sampling tool to the one or more depths within the wellbore based at least in part on the relative shift table. The system may include a fluid sampling tool disposed in a wellbore to create a correlation log and an information handling system connected to the fluid sampling tool.
Opening claim text (preview).
What is claimed is: 1. A method comprising: reviewing an openhole log; identifying one or more depths within a wellbore for testing from the openhole log; disposing a fluid sampling tool into the wellbore; creating a correlation log with the fluid sampling tool; depth-matching the correlation log to the openhole log to create a relative shift table; and moving the fluid sampling tool to the one or more depths within the wellbore based at least in part on the relative shift table. 2. The method of claim 1 , wherein the depth-matching is performed with a window-based correlation, an edge-based matching, or a dynamic time warping. 3. The method of claim 2 , wherein the window-based correlation, the edge-based matching, or the dynamic time warping are used in a machine learning model to estimate one or more relative shifts that populate the relative shift table. 4. The method of claim 2 , wherein the window-based correlation comprises: overlapping the correlation log and the openhole log; computing a correlation between the correlation log and the openhole log; identifying a depth shift to correlate between the correlation log and the openhole log; interpolating and extrapolating additional depth points based at least in part on the depth shift; and applying a depth correction to the correlation log. 5. The method of claim 2 , wherein the edge-based matching comprises: identifying one or more significant features in the correlation log and the openhole log; computing one or more depth shifts based at least in part on the one or more significant features between the correlation log and the openhole log; computing a correlation between the correlation log and the openhole log using the one or more depth shifts; interpolating and extrapolating additional depth points based at least in part on the correlation; and applying a depth correction to the correlation log. 6. The method of claim 1 , the openhole log is formed from one or more gamma ray measurements, one or more resistivity measurements, one or more density measurements, one or more neutron measurements, or one or more borehole images. 7. The method of claim 1 , wherein the correlation log is formed in real-time. 8. The method of claim 7 , wherein the depth-matching is performed in real-time based at least in part on the correlation log. 9. The method of claim 1 , further comprising generating the correlation with a gamma ray sensor. 10. The method of claim 1 , further comprises aligning one or more significant features on the correlation log to the one or more significant features on the openhole log during the depth-matching. 11. The method of claim 1 , further comprising forming a dynamically calibrated depth panel from the relative shift table. 12. The method of claim 11 , further comprising landing the fluid sampling tool at the one or more depths when a difference between the dynamically calibrated depth panel and the one or more depths is below a threshold. 13. A system comprising: a fluid sampling tool disposed in a wellbore to create a correlation log; and an information handling system connected to the fluid sampling tool comprising at least one processing unit and at least one computer media to: identify one or more depths within the wellbore for testing using an openhole log; create the correlation log with the fluid sampling tool; depth-match the correlation log to the openhole log to create a relative shift table; and instruct the fluid sampling tool to move to the one or more depths within the wellbore based at least in part on the relative shift table. 14. The system of claim 13 , wherein the depth-match is performed with a window-based correlation, an edge-based matching, or a dynamic time warping. 15. The system of claim 14 , wherein the window-based correlation, the edge-based matching, or the dynamic time warping are used in a machine learning model to estimate one or more relative shifts that populate the relative shift table. 16. The system of claim 14 , wherein the information handling system further utilizes the window-based correlation to: overlap the correlation log and the openhole log; compute a correlation between the correlation log and the openhole log; identify a depth shift to correlate between the correlation log and the openhole log; interpolate and extrapolate additional depth points based at least in part on the depth shift; and apply a depth correction to the correlation log. 17. The system of claim 14 , wherein the information handling system further utilizes the edge-based matching to: identify one or more significant features in the correlation log and the openhole log; compute one or more depth shifts based at least in part on the one or more significant features between the correlation log and the openhole log; compute a correlation between the correlation log and the openhole log using the one or more depth shifts; interpolate and extrapolate additional depth points based at least in part on the correlation; and apply a depth correction to the correlation log. 18. The system of claim 13 , wherein the openhole log is formed from one or more gamma ray measurements, one or more resistivity measurements, one or more density measurements, one or more neutron measurements, or one or more borehole images. 19. The system of claim 13 , wherein the correlation log is formed in real-time and wherein the depth-match is performed in real-time based at least in part on the correlation log. 20. The system of claim 13 , wherein the information handling system further forms a dynamically calibrated depth panel from the relative shift table.
specially adapted for well-logging · CPC title
Fuzzy logic, artificial intelligence, neural networks or the like · CPC title
Obtaining fluid samples or testing fluids, in boreholes or wells · CPC title
Measuring depth or liquid level · CPC title
Raw oil, drilling fluid or polyphasic mixtures · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.