Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Ứng dụng Dữ liệu Mềm trong Ước lượng Tài nguyên Hạt nhân
Tóm tắt
Khoáng sản và kim loại đóng vai trò cực kỳ quan trọng trong xã hội của chúng ta, và nguồn tài nguyên khoáng sản trên và dưới đáy đại dương sâu đại diện cho một tiềm năng khổng lồ. Việc quyết định xem khai thác từ đáy đại dương sâu có khả thi về mặt tài chính, môi trường và công nghệ hay không cần phải có thông tin. Do độ sâu lớn và điều kiện khắc nghiệt, việc thu thập thông tin này tốn kém và tiêu tốn thời gian và tài nguyên. Do đó, điều quan trọng là sử dụng mọi dữ liệu một cách tối ưu. Trong nghiên cứu này, dữ liệu được thu thập từ hình ảnh và kiến thức chuyên gia đã được sử dụng để ước lượng sự phong phú tối thiểu và tối đa của hạt nhân tại các vị trí hình ảnh từ một khu vực trong vùng Clarion-Clipperton ở phía Bắc Thái Bình Dương. Từ các giá trị tối thiểu và tối đa, lõi hộp và sự tương quan không gian được định lượng thông qua variogram, một kỳ vọng có điều kiện và sự không chắc chắn liên quan đã được thu được thông qua bộ mẫu Gibbs. Kỳ vọng có điều kiện và sự không chắc chắn đã được sử dụng cùng với dữ liệu phong phú giả định từ các lõi hộp trong một bài tập kriging để thu được ước lượng tốt hơn về sự phong phú theo từng khối. Việc đánh giá chất lượng của các ước lượng được thực hiện dựa trên tiêu chí khoảng cách và trên các chỉ số chất lượng kriging như độ dốc hồi quy và trọng số trung bình. Từ các vị trí hình ảnh gốc, các cấu hình hình ảnh thay thế đã được thử nghiệm và cho thấy rằng các lựa chọn thay thế như vậy tạo ra các ước lượng tốt hơn, mà không tốn thêm chi phí. Các cải tiến trong tương lai sẽ tập trung vào việc nâng cao ước lượng của các giá trị tối thiểu và tối đa tại các vị trí hình ảnh.
Từ khóa
#Khai thác khoáng sản #tài nguyên nodule #kriging #Gibbs sampler #đại dương sâuTài liệu tham khảo
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