Inpainting borehole images using Generative Adversarial Networks
In this paper, we propose a GAN-based approach for gap filling in borehole images created by wireline microresistivity imaging tools. The proposed method utilizes a generator, global discriminator, and local discriminator to inpaint the missing regions of the image. The generator is based on an auto...
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Published in | arXiv.org |
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Abstract | In this paper, we propose a GAN-based approach for gap filling in borehole images created by wireline microresistivity imaging tools. The proposed method utilizes a generator, global discriminator, and local discriminator to inpaint the missing regions of the image. The generator is based on an auto-encoder architecture with skip-connections, and the loss function used is the Wasserstein GAN loss. Our experiments on a dataset of borehole images demonstrate that the proposed model can effectively deal with large-scale missing pixels and generate realistic completion results. This approach can improve the quantitative evaluation of reservoirs and provide an essential basis for interpreting geological phenomena and reservoir parameters. |
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AbstractList | In this paper, we propose a GAN-based approach for gap filling in borehole images created by wireline microresistivity imaging tools. The proposed method utilizes a generator, global discriminator, and local discriminator to inpaint the missing regions of the image. The generator is based on an auto-encoder architecture with skip-connections, and the loss function used is the Wasserstein GAN loss. Our experiments on a dataset of borehole images demonstrate that the proposed model can effectively deal with large-scale missing pixels and generate realistic completion results. This approach can improve the quantitative evaluation of reservoirs and provide an essential basis for interpreting geological phenomena and reservoir parameters. |
Author | Belmeskine, Rachid Abed Benaichouche |
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Snippet | In this paper, we propose a GAN-based approach for gap filling in borehole images created by wireline microresistivity imaging tools. The proposed method... |
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SubjectTerms | Boreholes Coders Discriminators Generative adversarial networks Reservoirs |
Title | Inpainting borehole images using Generative Adversarial Networks |
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