Edge detection of mineral bodies (deposits) using curvature gravity gradient tensor

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Moazam Sahar; AGHAJANI HAMID; Rezaie Mohammad

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Journal: JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING Year:2019 | Volume:9 | Issue:19 Page(s): 101-111

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Title

Edge detection of mineral bodies (deposits) using curvature gravity gradient tensor

Author(s)

Moazam Sahar | AGHAJANI HAMID | Rezaie Mohammad | Issue Writer Certificate

Keywords

Chromite

Gravity

Tensor

Edge detection

Tilt angle

Camaguey

Abstract

Summary: Chromite exploration is really important in mineral exploration. Gravity method is really important in Chromite exploration. Edge detection methods are used to determine lenses of Chromite. In this paper, we used the curvature Gravity gradient Tensor (CGGT) along with the Tilt angle method to detect Chromite lenses. Application of the methods on synthetic and real Gravity data showed that the CGGT can determine the edges of Chromite lenses better than the Tilt angle method. Introduction: Chromite is a strategic mineral. Therefore, the exploration of Chromite mineral reserves is the main mineral exploration priorities. Chromite has a marked density contrast with the host rock, so the Gravity method can be applied for exploration of the Chromite ore bodies. The boreholes locations are usually determined after finding the edges of the Chromite lenses by Edge detection of the Gravity anomalies. There are various Edge detection methods. Most of the edge enhancement techniques are interpreted qualitatively. The Tilt angle method is a traditional method that can detect edges of subsurface structures quantitatively. The value of Tilt angle is zero above edges of subsurface bodies. The curvature Gravity gradient Tensor (CGGT) was also used to interpret the geological structure quantitatively. The value of eigenvalues of CGGT are zero above edges of subsurface bodies. In this paper, we used CGGT for Edge detection of Chromite lenses. Methodology and Approaches: In order to obtain CGGT, at first, horizontal vector gradients of Gravity gradient Tensors are computed from the vertical component of Gravity data with a Fourier transform technique. Then the eigenvalues of CGGT are obtained. The large eigenvalue determines the edges of negative density bodies while the small eigenvalue only can be used to outline edges of positive density bodies. The Chromite has positive density contrast with the host rock and produce positive Gravity anomaly. Therefore, we choose the small eigenvalue to outline edges of the Chromite lenses. Finally, the Tilt angle is also applied to compare with the CGGT. Results and Conclusions: The robustness of the codes used for the edge enhancement is tested with Gravity field anomaly map caused by four prisms of synthetic bodies. The results indicated that the proposed method can enhance the edges of the synthetic bodies with zero contour of the small eigenvalue of the CGGT. Then, the proposed method has been applied on the real Gravity data from Chromite deposits In Camaguey province, Cuba. The results showed that the zero contour of the small eigenvalue of the CGGT can outline the edges of synthetic bodies and Chromite lenses better than the zero contour of the Tilt angle method. Therefore, we can use the small eigenvalue of the CGGT to detect edges of Chromite lenses precisely.

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APA: Copy

Moazam, Sahar, AGHAJANI, HAMID, & Rezaie, Mohammad. (2019). Edge detection of mineral bodies (deposits) using curvature gravity gradient tensor. JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING, 9(19 ), 101-111. SID. https://sid.ir/paper/266099/en

Vancouver: Copy

Moazam Sahar, AGHAJANI HAMID, Rezaie Mohammad. Edge detection of mineral bodies (deposits) using curvature gravity gradient tensor. JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING[Internet]. 2019;9(19 ):101-111. Available from: https://sid.ir/paper/266099/en

IEEE: Copy

Sahar Moazam, HAMID AGHAJANI, and Mohammad Rezaie, “Edge detection of mineral bodies (deposits) using curvature gravity gradient tensor,” JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING, vol. 9, no. 19 , pp. 101–111, 2019, [Online]. Available: https://sid.ir/paper/266099/en

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