Speaker: Dr. Mengli Zhang, Research Associate, Center for Gravity, Electrical, and Magnetic Studies (CGEM), Colorado School of Mines
Title: Efficient geophysical data acquisition using ergodic sampling: Non-linear relationship between information sampling ability (ISA) and number of samples
Date: Thursday February 23, 2022
Time: 4:30pm to 5:30pm PST
Location: Virtual. Zoom link will be distributed via our newsletter in advance of the talk. Contact info@bcgsonline.org if you would like to attend but did not receive the newsletter with link (sent February 21, 2023).
Abstract:
Geophysicists use difference tools such as data display, modeling, and inversion to image subsurface of the earth. The denser the data are, the more details of earth model we can obtain. The price we pay for denser data is of course the higher cost for acquisition, especially for 3D data. We may default to an implicit assumption that the resolution of our earth model is linearly dependent upon the number of samples we can collect for geophysical data. This assumption may be rooted in Nyquist sampling theory. However, Nyquist sampling theory is a sufficient but not necessary condition. We have re-examined the necessity of such dense sampling in geophysical data acquisition and developed an ergodic sampling method and shows that the number of samples has a non-linear relationship with the information sampling ability (ISA). In contrast to Nyquist sampling, which requires a sufficient but larger than necessary sample set, ergodic sampling only acquires the core subset of samples that is both necessary and sufficient to gather the same information. Therefore, ergodic sampling can significantly decrease the number of samples compared with Nyquist sampling. We present our new sampling theory and demonstrate its application in the geophysical data acquisition. Our simulation and field data example show that the cost can be reduced by a factor up to 10. Equivalently, this result also means that it is possible to acquire 10 times more information when the same number of samples used in the traditional equi-spaced sampling is deployed using the ergodic sampling strategy.
Bio:
Dr. Mengli Zhang is a Research Associate in the Department of Geophysics at Colorado School of Mines. She is a geophysicist specialized in optimization of the exploration cycle from acquisition, interpretation, to discovery by incorporating economic factors. She is also an expert on efficient and economical multi-geophysical data acquisition using ergodic sampling theory. She obtained her BS in Information Engineering and MS degree in Information and Communication Systems from Xi’an Jiaotong University in China. She earned an MS degree in Geoscience from the University of Texas at Dallas, USA, and PhD degree in Geophysics from Colorado School of Mines. She has 10 years of industry experiences, first as a research geophysicist and then as a project manager and as Chief Geophysicist in the eastern Ordos Basin for China National Petroleum Corporation, where she applied information analyses to increase gas reservoir discoveries. She worked closely with geologists to select locations of more than 500 drilled wells, perform post-drilling analyses throughout the life cycle of wells including the production stage, and to improve interpretation and targeting methodology based on drilling and production results. Her current research has applications to the information-based economic geophysical data acquisition, which has the potential to significantly reduce the cost of exploration for energy and metals and to accelerate discoveries.