| Abstract Submission No. | ABS-4.1-0227 |
| Title of Abstract | Lithological Boundary Identification From Well Log Data Using Wavelet Transform |
| Authors | Pritam Kundu* |
| Organisation | IIT (ISM) Dhanbad |
| Address | Diamond Hostel, IIT (ISM) Dhanbad Dhanbad, Jharkhand, India Pincode: 826004 E-mail: 23mc0060@iitism.ac.in |
| Country | India |
| Presentation | Poster |
| Abstract | We can get various petrophysical information of the subsurface from geophysical log data which used to provide us an advantage in geological interpretation like lithological succession, sedimentary deposition pattern etc, at drilling location. The process of lithological boundary identification becomes more difficult due to several factors like washout, caving, abnormal mud cake, bad borehole conditions, and discontinuity in borehole data. Previously, Walsh Transform, Discrete Fourier Transform, Fast Fourier Transform have been used by many scientists as a mathematical tool and have identified bed-boundaries from well log data. In this study my goal is to develop a practical system or workflow for lithological boundary detection with a comparatively higher resolution by using Wavelet Transform for signal processing and multi log integration for boundary picking. A suitable level of decomposition and appropriate mother wavelet has to be selected for Wavelet Transform through an error evaluation as this will help us to reduce the noise while preserving the geological information. The abrupt changes in the decomposed signal will be detected via a weighted picking algorithm by assigning separate weightage to each decomposed log data. Basic logs like as gamma ray (GR), bulk density (ρb), neutron porosity (NΦ), resistivity (Rt), and photoelectric factor (PEF) will be used for this purpose. Final boundaries will be selected by correlating the previously picked abrupt changes and available stratigraphic information from the core completion report. Lithological boundary detection has several applications in reservoir estimation, well to well correlation, resource estimation and mining etc. This approach is expected to be more efficient in boundary identification than the manual picking and single log methods, and can be used in both academic research and industry purpose. |
| Keywords | Wavelet Transform, Borehole Geophysics, Logging Techniques, Lithological Boundary Detection |