Sensitivity of Marine Controllable Source Electromagnetic Soundings for Identifying Plume Migration in Offshore CO_(2) Storage

Offshore carbon dioxide(CO_(2)) storage is an effective method for reducing greenhouse gas emissions. However, when using traditional seismic wave methods to monitor the migration of sequestration CO_(2) plumes, the characteristics of wave velocity changes tend to become insignificant beyond a certain limit. In contrast, the controllable source electromagnetic method(CSEM) remains highly sensitive to resistivity changes. By simulating different CO_(2) plume migration conditions, we established the relevant models and calculated the corresponding electric field response characteristic curves, allowing us to analyze the CSEM's ability to monitor CO_(2) plumes. We considered potential scenarios for the migration and diffusion of offshore CO_(2) storage, including various burial depths, vertical extension diffusion, lateral extension diffusion,multiple combinations of lateral intervals, and electric field components. We also obtained differences in resistivity inversion imaging obtained by CSEM to evaluate its feasibility in monitoring and to analyze all the electric field(Ex, Ey, and Ez) response characteristics. CSEM has great potential in monitoring CO_(2) plume migration in offshore saltwater reservoirs due to its high sensitivity and accuracy. Furthermore, changes in electromagnetic field response reflect the transport status of CO_(2) plumes, providing an important basis for monitoring and evaluating CO_(2)transport behavior during storage processes.

A robust behavior of Feed Forward Back propagation algorithm of Artificial Neural Networks in the application of vertical electrical sounding data inversion

The applications of intelligent techniques have increased exponentially in recent days to study most of the non-linear parameters. In particular, the behavior of earth resembles the non- linearity applications. An efficient tool is needed for the interpretation of geophysical parameters to study the subsurface of the earth. Artificial Neural Networks （ANN） perform certain tasks if the structure of the network is modified accordingly for the purpose it has been used. The three most robust networks were taken and comparatively analyzed for their performance to choose the appropriate network. The single- layer feed-forward neural network with the back propagation algorithm is chosen as one of the well- suited networks after comparing the results. Initially, certain synthetic data sets of all three-layer curves have been taken tk^r training the network, and the network is validated by the field datasets collected from Tuticorin Coastal Region （78°7＇30＂E and 8°48＇45＂N）, Tamil Nadu, India. The interpretation has been done successfully using the corresponding learning algorithm in the present study. With proper training of back propagation networks, it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data concerning the synthetic data trained earlier in the appropriate network. The network is trained with more Vertical Electrical Sounding （VES） data, and this trained network is demon- strated by the field data. Groundwater table depth also has been modeled.

Three-dimensional forward modeling and inversion of borehole-to-surface electrical imaging with different power sources

Borehole-to-surface electrical imaging （BSEI） uses a line source and a point source to generate a stable electric field in the ground. In order to study the surface potential of anomalies, three-dimensional forward modeling of point and line sources was conducted by using the finite-difference method and the incomplete Cholesky conjugate gradient （ICCG） method. Then, the damping least square method was used in the 3D inversion of the formation resistivity data. Several geological models were considered in the forward modeling and inversion. The forward modeling results suggest that the potentials generated by the two sources have different surface signatures. The inversion data suggest that the low- resistivity anomaly is outlined better than the high-resistivity anomaly. Moreover, when the point source is under the anomaly, the resistivity anomaly boundaries are better outlined than when using a line source.

A new method for earthquake prediction by earth-resistivity measurements

It is difficult to predict earthquakes by earthresistivity measurement with single-poleseparation. Taking a shallow seated horizontally stratification model, we developed a new measurement system with multipoleseparations and its corresponding inversion technique of the earth-resistivity to improve the prediction efficiency. Long-term experiments and investigations at several stations show that the new method based on resisti-vity variations at the bottom of shollow seated stratified medium is obviously superior to that directly based on the earth-resistivity itself.

Applications of variogram modeling to electrical resistivity data for the occurrence and distribution of saline groundwater in Domail Plain,northwestern Himalayan fold and thrust belt,Pakistan

This paper studies electrical resistivity dataset acquired for a groundwater study in the Domail Plain in the northwestern Himalayan section of Pakistan. Through a combination of geostatistical analysis,geophysical inversion and visualization techniques,it is possible to re-model and visualize the single dimension resistivity data into 2D and 3D space.The variogram models are utilized to extend the interpretation of the data and to distinguish individual lithologic units and the occurrence of saline water within the subsurface. The resistivity data has been calibrated with the lithological logs taken from the available boreholes. As such the alluvial system of the Domail Plain has formed during episodes of local tectonic activity with fluvial erosion and depositionyielding coarse sediments with high electrical resistivities near to the mountain ranges and finer sediments with medium to low electrical resistivities which tend to settle in the basin center. Thus a change is depositional setting happened from basin lacustrine environment to flash flooding during the Himalayan orogeny. The occurrence of rock salt in the northern mountains has imparted a great influence on the groundwater quality of the study area. The salt is dissolved by water which infiltrates into the subsurface through the water channels. Variogram aided gridding of resistivity data helps to identify the occurrence and distribution of saline water in the subsurface.