Shaping optimal transmitter waveforms for marine CSEM surveys

Geophysics ◽  
2008 ◽  
Vol 73 (3) ◽  
pp. F97-F104 ◽  
Author(s):  
Rune Mittet ◽  
Tor Schaug-Pettersen
Keyword(s):  
Optimization Problem ◽  
Maximum Energy ◽  
Frequency Spectra ◽  
Square Wave ◽  
Depth Migration ◽  
Controlled Source ◽  
Switching Times ◽  
Multiple Frequencies ◽  
Marine Csem ◽  
And Inversion

The square wave is frequently used as the transmitter waveform in marine controlled-source electromagnetics (CSEM) surveys. This waveform has the advantage of transferring maximum energy to the subsurface because the transmitter current is running at its peak amplitude at all times. However, a limitation of the square wave is that most of the transmitted energy is in the first harmonic. Processing methods such as depth migration and inversion have shown improved results if a transmitter waveform with substantial amounts of energy at multiple frequencies is used. We propose a method for designing transmitter waveforms where current amplitudes as a function of frequency can have an approximate predefined or desired distribution. At the same time, we require that the transmitter operate at its peak current at all times to maximize the energy transferred to the subsurface. To obtain the desired current spectra, the number of switching times in a period is allowed to be larger than two, which is the number of switching times per period for a standard square wave. The method is based on matching the desired frequency spectra with the spectra obtained from these generalized square waves. This optimization problem is solved by a Monte Carlo method. The resultant waveforms can be used for an electric-dipole transmitter.

Seismic wave propagation concepts applied to the interpretation of marine controlled-source electromagnetics

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. E63-E81 ◽  
Author(s):  
Rune Mittet
Keyword(s):  
Seismic Data ◽  
Maxwell Equations ◽  
Seismic Wave Propagation ◽  
Finite Difference Schemes ◽  
Data Types ◽  
Controlled Source ◽  
Electromagnetic Data ◽  
Inverse Transform ◽  
Refraction Seismic ◽  
Marine Csem

Concepts such as reflections, refractions, diffractions, and transmissions are very useful for the interpretation of seismic data. Moreover, these concepts play a key role in the design of processing algorithms for seismic data. Currently, however, the same concepts are not widely used for the analysis and interpretation of marine controlled-source electromagnetic (CSEM) data. Connections between seismic and marine CSEM data are established by analytically transforming the diffusive Maxwell equations to wave-domain Maxwell equations. Seismic data and wave-domain electromagnetic data are simulated with 3D finite-difference schemes. The two data types are similar; however, the wave-domain electromagnetic data must be transformed back to the diffusive domain to properly describe realistic field propagation in the earth. We analyzed the inverse transform from the wave domain to the diffusive domain. Concepts like reflections, refractions, diffractions and transmissions were found to be valid also for marine CSEM data but the properties of the inverse transform favored refracted and guided events over reflected and diffracted events. In this sense, marine CSEM data were found to be similar to refraction seismic data.

2D marine controlled-source electromagnetic modeling: Part 2 — The effect of bathymetry

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. WA63-WA71 ◽  
Author(s):  
Yuguo Li ◽  
Steven Constable
Keyword(s):  
Finite Element ◽  
Numerical Modeling ◽  
Data Sets ◽  
Electromagnetic Modeling ◽  
Seafloor Topography ◽  
Transmission Frequency ◽  
Controlled Source ◽  
Magnetic Components ◽  
Marine Csem ◽  
Conductivity Contrast

Marine controlled-source electromagnetic (CSEM) data are strongly affected by bathymetry because of the conductivity contrast between seawater and the crust below the seafloor. We simulate the marine CSEM response to 2D bathymetry using our new finite element (FE) code, and our numerical modeling shows that all electric and magnetic components are influenced by bathymery, but to different extents. Bathymetry effects depend upon transmission frequency, seabed conductivity, seawater depth, transmitter-receiver geometry, and roughness of the seafloor topography. Bathymetry effects clearly have to be take into account to avoid the misinterpretation of marine CSEM data sets.

The feasibility of reservoir monitoring using time-lapse marine CSEM

Geophysics ◽  
2009 ◽  
Vol 74 (2) ◽  
pp. F21-F29 ◽  
Author(s):  
Arnold Orange ◽  
Kerry Key ◽  
Steven Constable
Keyword(s):  
Extraction Efficiency ◽  
Time Lapse ◽  
Small Signal ◽  
Controlled Source ◽  
Hydrocarbon Reservoir ◽  
Reservoir Monitoring ◽  
Fluid Properties ◽  
Reservoir Geometry ◽  
Marine Csem ◽  
Percent Accuracy

Monitoring changes in hydrocarbon reservoir geometry and pore-fluid properties that occur during production is a critical part of estimating extraction efficiency and quantifying remaining reserves. We examine the applicability of the marine controlled-source electromagnetic (CSEM) method to the reservoir-monitoring problem by analyzing representative 2D models. These studies show that CSEM responses exhibit small but measureable changes that are characteristic of reservoir-depletion geometry, with lateral flooding producing a concave-up depletion-anomaly curve and bottom flooding producing a concave-down depletion-anomaly curve. Lateral flooding is also revealed by the spatial-temporal variation of the CSEM anomaly, where the edge of the response anomaly closely tracks the retreating edge of the flooding reservoir. Measureable changes in CSEM responses are observed when 10% of the resistive reservoir is replaced by conductive pore fluids. However, to avoid corrupting the relatively small signal changes associated with depletion, the acquisition geometry must be maintained to a fraction of a percent accuracy. Additional factors, such as unknown nearby seafloor inhomogeneities and variable seawater conductivity, can mask depletion anomalies if not accounted for during repeat monitoring measurements. Although addressing these factors may be challenging using current exploration CSEM practices, straightforward solutions such as permanent monuments for seafloor receivers and transmitters are available and suggest the method could be utilized with present-day technology.

scholarly journals Gaussian Process Methodology for Multi-Frequency Marine Controlled-Source Electromagnetic Profile Estimation in Isotropic Medium

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 661 ◽  
Author(s):  
Muhammad Naeim Mohd Aris ◽  
Hanita Daud ◽  
Sarat Chandra Dass ◽  
Khairul Arifin Mohd Noh
Keyword(s):  
Gaussian Process ◽  
Computational Cost ◽  
Computer Experiment ◽  
Controlled Source ◽  
Uncertainty Measurement ◽  
Process Methodology ◽  
Mathematical Equations ◽  
Marine Csem ◽  
Profile Estimation ◽  
Gp Model

The marine controlled-source electromagnetic (CSEM) technique is an application of electromagnetic (EM) waves to image the electrical resistivity of the subsurface underneath the seabed. The modeling of marine CSEM is a crucial and time-consuming task due to the complexity of its mathematical equations. Hence, high computational cost is incurred to solve the linear systems, especially for high-dimensional models. Addressing these problems, we propose Gaussian process (GP) calibrated with computer experiment outputs to estimate multi-frequency marine CSEM profiles at various hydrocarbon depths. This methodology utilizes prior information to provide beneficial EM profiles with uncertainty quantification in terms of variance (95% confidence interval). In this paper, prior marine CSEM information was generated through Computer Simulation Technology (CST) software at various observed hydrocarbon depths (250–2750 m with an increment of 250 m each) and different transmission frequencies (0.125, 0.25, and 0.5 Hz). A two-dimensional (2D) forward GP model was developed for every frequency by utilizing the marine CSEM information. From the results, the uncertainty measurement showed that the estimates were close to the mean. For model validation, the calculated root mean square error (RMSE) and coefficient of variation (CV) proved in good agreement between the computer output and the estimated EM profile at unobserved hydrocarbon depths.

Sign in / Sign up

Export Citation Format

Share Document