scholarly journals Reverse time migration (RTM) imaging of iron oxide deposits in the Ludvika mining area, Sweden

Solid Earth ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1707-1718
Author(s):  
Yinshuai Ding ◽  
Alireza Malehmir
Keyword(s):  
Iron Oxide ◽  
Large Scale ◽  
Random Noise ◽  
Mining Area ◽  
Mineral Deposits ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Near Surface ◽  
Time Migration ◽  
Seismic Methods

Abstract. To discover or delineate mineral deposits and other geological features such as faults and lithological boundaries in their host rocks, seismic methods are preferred for imaging the targets at great depth. One major goal for seismic methods is to produce a reliable image of the reflectors underground given the typical discontinuous geology in crystalline environments with low signal-to-noise ratios. In this study, we investigate the usefulness of the reverse time migration (RTM) imaging algorithm in hardrock environments by applying it to a 2D dataset, which was acquired in the Ludvika mining area of central Sweden. We provide a how-to solution for applications of RTM in future and similar datasets. When using the RTM imaging technique properly, it is possible to obtain high-fidelity seismic images of the subsurface. Due to good amplitude preservation in the RTM image, the imaged reflectors provide indications to infer their geological origin. In order to obtain a reliable RTM image, we performed a detailed data pre-processing flow to deal with random noise, near-surface effects, and irregular receiver and source spacing, which can downgrade the final image if ignored. Exemplified with the Ludvika data, the resultant RTM image not only delineates the iron oxide deposits down to 1200 m depth as shown from previous studies, but also provides a better inferred ending of sheet-like mineralization. Additionally, the RTM image provides much-improved reflection of the dike and crosscutting features relative to the mineralized sheets when compared to the images produced by Kirchhoff migration in the previous studies. Two of the imaged crosscutting features are considered to be crucial when interpreting large-scale geological structures at the site and the likely disappearance of mineralization at depth. Using a field dataset acquired in hardrock environment, we demonstrate the usefulness of RTM imaging workflows for deep targeting mineral deposits.

scholarly journals Reverse time migration (RTM) imaging of iron-oxide deposits in the Ludvika mining area, Sweden

2020 ◽  
Author(s):  
Yinshuai Ding ◽  
Alireza Malehmir
Keyword(s):  
Iron Oxide ◽  
Large Scale ◽  
Mining Area ◽  
Mineral Deposits ◽  
Great Level ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Imaging Algorithm ◽  
Time Migration ◽  
Seismic Methods

Abstract. To discover or delineate mineral deposits and other geological features such as faults and lithological boundaries in their host rocks, seismic methods are a qualified choice, given their resolution power at depth. One major goal for seismic methods is to produce a reliable image of the subsurface given the typical discontinuous geology in crystalline environment with low signal-to-noise ratio. In this study, we investigate the usefulness of reverse time migration (RTM) imaging algorithm in hardrock environment by applying it to a legacy 2D dataset, which was acquired in the Ludvika mining area of central Sweden. We provide a how-to solution for applications of RTM in future and similar datasets. When using the RTM imaging technique properly, it is possible to obtain high-fidelity seismic images of the subsurface. Due to good amplitude preservation in the RTM image, the imaged reflectors provide indications to infer their geological origin. Aside from the chosen seismic imaging algorithm, we illustrate that two other important factors for successful RTM imaging workflows are the suitable acquisition and careful data pre-processing. Exemplified with the Ludvika legacy data, the RTM method allows imaging the iron-oxide deposits at a great level of detail down to 1200 m depth as shown from previous studies. It also provides much-improved images of the lithological contacts and crosscutting features relative to the mineralized sheets. Some of the imaged crosscutting features are considered to be crucial when interpreting large-scale geological structures of the site and the likely disappearance of mineralization at depth. The RTM imaging workflows have the potential to be used on hardrock seismic data and for deep targeting mineral deposits, a key message we would like to deliver in this article.

scholarly journals 3D Imaging of Geothermal Faults from a Vertical DAS Fiber at Brady Hot Spring, NV USA

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1401 ◽  
Author(s):  
Whitney Trainor-Guitton ◽  
Antoine Guitton ◽  
Samir Jreij ◽  
Hayden Powers ◽  
Bane Sullivan
Keyword(s):  
Hot Spring ◽  
Random Noise ◽  
3D Models ◽  
Seismic Survey ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Geothermal Exploration ◽  
3D Space ◽  
Time Migration ◽  
Middle West

In March 2016, arguably the most ambitious 4D (3D space + over time) active-source seismic survey for geothermal exploration in the U.S. was acquired at Brady Natural Laboratory, outside Fernley, Nevada. The four-week experiment included 191 vibroseis source locations, and approximately 130 m of distributed acoustic sensing (DAS) in a vertical well, located at the southern end of the survey area. The imaging of the geothermal faults is done with reverse time migration of the DAS data for both P-P and P-S events in order to generate 3D models of reflectivity, which can identify subsurface fault locations. Three scenarios of receiver data are explored to investigate the reliability of the reflectivity models obtained: (1) Migration of synthetic P-P and P-S DAS data, (2) migration of the observed field DAS data and (3) migration of pure random noise to better assess the validity of our results. The comparisons of the 3D reflectivity models from these three scenarios confirm that sections of three known faults at Brady produce reflected energy observed by the DAS. Two faults that are imaged are ~1 km away from the DAS well; one of these faults (middle west-dipping) is well-constructed for over 400 m along the fault’s strike, and 300 m in depth. These results confirm that the DAS data, together with an imaging engine such as reverse time migration, can be used to position important geothermal features such as faults.

scholarly journals Enhancing the Near-Surface Image Using Duplex-Wave Reverse Time Migration

2019 ◽  
Author(s):  
Ghada Sindi ◽  
Tariq Alkhalifah ◽  
Tong Fei ◽  
Yi Luo
Keyword(s):  
Reverse Time ◽  
Reverse Time Migration ◽  
Near Surface ◽  
Time Migration ◽  
Surface Image

Reverse time migration from topography

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. S141-S152 ◽  
Author(s):  
Jeffrey Shragge
Keyword(s):  
Wave Propagation ◽  
Acoustic Wave ◽  
Data Acquisition ◽  
Velocity Variation ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Acoustic Wave Propagation ◽  
Lateral Velocity ◽  
Near Surface ◽  
Time Migration

Migration of seismic data from topography using methods based on finite-difference (FD) approximation to acoustic wave propagation commonly suffers from a number of imaging drawbacks due to the difficulty of applying FD stencils to irregular computational meshes. Altering the computational geometry from Cartesian to a topographic coordinate system conformal to the data acquisition surface can circumvent many of these issues. The coordinate transformation approach allows for acoustic wave propagation and the crosscorrelation and inverse-scattering imaging conditions to be posed and computed directly in topographic coordinates. Resulting reverse time migration (RTM) images may then be interpolated back to the Cartesian domain using the known inverse mapping. Orthogonal 2D topographic coordinates can be developed using known conformal mapping transforms and serve as the computational mesh for performing migration from topography. Impulse response tests demonstrate the accuracy of the 2D generalized acoustic wave propagation. RTM imaging examples show the efficacy of performing migration from topography directly from the data acquisition surface on topographic meshes and the ability to image complex near-surface structure even in the presence of strong lateral velocity variation.

Enhanced prestack depth imaging of wide-azimuth data from the Gulf of Mexico: A case history

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB79-WB86 ◽  
Author(s):  
Xuening Ma ◽  
Bin Wang ◽  
Cristina Reta-Tang ◽  
Wilfred Whiteside ◽  
Zhiming Li
Keyword(s):  
Image Quality ◽  
Gulf Of Mexico ◽  
Large Scale ◽  
Velocity Model ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Delayed Imaging ◽  
Data Set ◽  
Depth Imaging ◽  
Time Migration

We present a case study of enhanced imaging of wide-azimuth data from the Gulf of Mexico utilizing recent technologies; and we discuss the resulting improvements in image quality, especially in subsalt areas, relative to previous results. The input seismic data sets are taken from many large-scale wide-azimuth surveys and conventional narrow-azimuth surveys located in the Mississippi Canyon and Atwater Valley areas. In the course of developing the enhanced wide azimuth processing flow, the following three key steps are found to have the most impact on improving subsalt imaging: (1) 3D true azimuth surface-related multiple elimination (SRME) to remove multiple energy, in particular, complex multiples beneath salt; (2) reverse-time migration (RTM) based delayed imaging time (DIT) scans to update the complex subsalt velocity model; and (3) tilted transverse isotropic (TTI) RTM to improve image quality. Our research focuses on the depth imaging aspects of the project, with particular emphasis on the application of the DIT scanning technique. The DIT-scan technique further improves the accuracy of the subsalt velocity model after conventional ray-based subsalt tomography has been performed. We also demonstrate the uplift obtained by acquiring a wide-azimuth data set relative to a standard narrow-azimuth data set, and how orthogonal wide-azimuth is able to enhance the subsalt illumination.

Receiver grouping strategies for hybrid Geometric-mean Reverse-time migration

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Tong Bai ◽  
Bin Lyu ◽  
Paul Williamson ◽  
Nori Nakata
Keyword(s):  
Time Reversal ◽  
Cross Correlation ◽  
Geometric Mean ◽  
Random Noise ◽  
Imaging Method ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Image Domain ◽  
Time Migration ◽  
Grouping Strategies

Geometric-mean Reverse-time migration (GmRTM), a powerful cross-correlation-based imaging method, generates higher-resolution source images and is more robust to noise compared to conventional time-reversal imaging. The price to pay is the higher computational costs. Alternatively, we can adopt hybrid strategies by dividing the receivers into different groups. Conventional time reversal (i.e., wavefield summation) is performed inside each group, followed by the application of cross-correlation imaging condition among different groups. Such hybrid strategies can retain the advantages of both GmRTM and time-reversal, and are often more practical than pure GmRTM. Yet, designing appropriate grouping strategy is not trivial. Here, we propose two grouping strategies (adjacent and scattered) and use synthetic and field-data examples to evaluate their performance with various group numbers. In addition to the spatial resolution of the source image, robustness to random noise is another important assessment criterion, for which we consider two distribution patterns, such as concentrated and scattered, of traces contaminated with strong random noise. We also evaluated their effectiveness to visualize events (in the image domain) that are not completely recorded by all receivers. Our comprehensive tests illustrate the respective advantages of the two grouping strategies.

Mapping subsurface karsts and voids using directional elastic wave packets

Geophysics ◽  
2021 ◽  
Vol 86 (6) ◽  
pp. S405-S416
Author(s):  
Yinshuai Ding ◽  
Hao Hu ◽  
Adel Malallah ◽  
Michael C. Fehler ◽  
Lianjie Huang ◽  
...  
Keyword(s):  
Wave Packet ◽  
Elastic Wave ◽  
Wave Packets ◽  
Random Noise ◽  
Velocity Model ◽  
Imaging Method ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Time Migration ◽  
The Difference

We have developed a new data-driven algorithm that uses directional elastic wave packets as seismic sources to image subsurface voids (i.e., cavities). Compared to a point source, the advantage of the new approach is that the wave packet illuminates only a small volume of the medium around the raypath to significantly reduce multiple scattering effects in the imaging. We take the difference of traces at identical source-receiver offsets from each of two neighboring source packets. The difference mainly contains the void scattering events but not the direct waves, the layer reflections, refractions, nor layer-related multiples. We use P-to-P and P-to-S scattered waves to locate the voids, and the results using scattered P- and S-waves can cross-validate each other to reduce the possibility of false detections. The directional wave packet can be numerically synthesized using existing shot gathers; therefore, no special physical source is required. We determine our method using data calculated using a boundary element method to model the seismic wavefield in an irregularly layered medium containing several empty voids. We test the robustness of our method using the same data but with 15% root-mean-square random noise added. Furthermore, we compare our method with the reverse time migration imaging method using the same data and find that our method provides superior results that are not dependent on the construction of a velocity model.

Fast image-domain target-oriented least-squares reverse time migration

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. A81-A86 ◽  
Author(s):  
Zeyu Zhao ◽  
Mrinal K. Sen
Keyword(s):  
Plane Wave ◽  
Least Squares ◽  
Large Scale ◽  
Green's Functions ◽  
Green’S Functions ◽  
Hessian Matrix ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Image Domain ◽  
Time Migration

We have developed a fast image-domain target-oriented least-squares reverse time migration (LSRTM) method based on applying the inverse or pseudoinverse of a target-oriented Hessian matrix to a migrated image. The image and the target-oriented Hessian matrix are constructed using plane-wave Green’s functions that are computed by solving the two-way wave equation. Because the number of required plane-wave Green’s functions is small, the proposed method is highly efficient. We exploit the sparsity of the Hessian matrix by computing only a couple of off-diagonal terms for the target-oriented Hessian, which further improves the computational efficiency. We examined the proposed LSRTM method using the 2D Marmousi model. We demonstrated that our method correctly recovers the reflectivity model, and the retrieved results have more balanced illumination and higher spatial resolution than traditional images. Because of the low cost of computing the target-oriented Hessian matrix, the proposed method has the potential to be applied to large-scale problems.

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