東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Quantitative prediction of blind ore...

Chen, Jianping.

Linked to FindBook

Google Book

Amazon

博客來

Quantitative prediction of blind ore deposits = theory and practice /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Quantitative prediction of blind ore deposits/ by Jianping Chen.
Reminder of title:	theory and practice /
Author:	Chen, Jianping.
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	xiii, 339 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Fundamentals of 2D Quantitative Forecasting in Mineral Resource Assessment -- 2D Quantitative Prediction Method of Mineral Resources -- Application Case 1: Quantitative Prediction of Copper Resources in the Southern Margin of the North China Craton -- Principles of 3D Quantitative Prediction of Mineral Resources -- 3D Quantitative Prediction Method of Mineral Resources -- Application Case 2: Predicting Metallogenic Potential in Shandong Province's Jiaojia Gold Belt Through 3D Modeling -- Application case 3: Geospatial Modeling, Predictive Analysis, and Assessment of the Laochang Ore Field in Gejiu, Yunnan: A 3D Approach to Metallogenic Features.
Contained By:	Springer Nature eBook
Subject:	Metallogenic provinces - Data processing. -
Online resource:	https://doi.org/10.1007/978-981-95-1770-1
ISBN:	9789819517701

Quantitative prediction of blind ore deposits = theory and practice /
Chen, Jianping.

Quantitative prediction of blind ore depositstheory and practice /[electronic resource] :by Jianping Chen. - Singapore :Springer Nature Singapore :2025. - xiii, 339 p. :ill., digital ;24 cm.

Introduction -- Fundamentals of 2D Quantitative Forecasting in Mineral Resource Assessment -- 2D Quantitative Prediction Method of Mineral Resources -- Application Case 1: Quantitative Prediction of Copper Resources in the Southern Margin of the North China Craton -- Principles of 3D Quantitative Prediction of Mineral Resources -- 3D Quantitative Prediction Method of Mineral Resources -- Application Case 2: Predicting Metallogenic Potential in Shandong Province's Jiaojia Gold Belt Through 3D Modeling -- Application case 3: Geospatial Modeling, Predictive Analysis, and Assessment of the Laochang Ore Field in Gejiu, Yunnan: A 3D Approach to Metallogenic Features.

This book systematically summarizes the theory and technical methods of two-dimensional and three-dimensional quantitative prediction and evaluation of deep mineral resources, and introduces case studies from different scales such as metallogenic regions, metallogenic belts and deposits. It is the accumulation of long-term experience in the combination of quantitative analysis, technology research and prospecting practice in metallogenic prediction. It combines scientific theories, software operations and case studies in its content arrangement to make the theory and technical methods more practical in directing practitioners. This book introduces a series of core technologies with independent intellectual property rights. The self-developed and integrated prediction and evaluation system introduced in this book shows a wide range of application prospects in practice. It has important theoretical significance and practical promotion value for cultivating interdisciplinary talents who are proficient in geology, mathematics and information technology.

ISBN: 9789819517701

Standard No.: 10.1007/978-981-95-1770-1doiSubjects--Topical Terms:

3803786
Metallogenic provinces
--Data processing.

LC Class. No.: TN263 / .C44 2025

Dewey Class. No.: 553.4

Quantitative prediction of blind ore deposits = theory and practice /
LDR:02736nmm a22003255a 4500 001 2422186
003 DE-He213
005 20251124120421.0
006 m d
007 cr nn 008maaau
008 260505s2025 si s 0 eng d
020 $a 9789819517701 $q (electronic bk.)
020 $a 9789819517695 $q (paper)
024 7 $a 10.1007/978-981-95-1770-1 $2 doi
035 $a 978-981-95-1770-1
040 $a GP $c GP
041 0 $a eng
050 4 $a TN263 $b .C44 2025
072 7 $a RBG $2 bicssc
072 7 $a SCI031000 $2 bisacsh
072 7 $a RBG $2 thema
082 0 4 $a 553.4 $2 23
090 $a TN263 $b .C518 2025
100 1 $a Chen, Jianping. $3 711107
245 1 0 $a Quantitative prediction of blind ore deposits $h [electronic resource] : $b theory and practice / $c by Jianping Chen.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2025.
300 $a xiii, 339 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Fundamentals of 2D Quantitative Forecasting in Mineral Resource Assessment -- 2D Quantitative Prediction Method of Mineral Resources -- Application Case 1: Quantitative Prediction of Copper Resources in the Southern Margin of the North China Craton -- Principles of 3D Quantitative Prediction of Mineral Resources -- 3D Quantitative Prediction Method of Mineral Resources -- Application Case 2: Predicting Metallogenic Potential in Shandong Province's Jiaojia Gold Belt Through 3D Modeling -- Application case 3: Geospatial Modeling, Predictive Analysis, and Assessment of the Laochang Ore Field in Gejiu, Yunnan: A 3D Approach to Metallogenic Features.
520 $a This book systematically summarizes the theory and technical methods of two-dimensional and three-dimensional quantitative prediction and evaluation of deep mineral resources, and introduces case studies from different scales such as metallogenic regions, metallogenic belts and deposits. It is the accumulation of long-term experience in the combination of quantitative analysis, technology research and prospecting practice in metallogenic prediction. It combines scientific theories, software operations and case studies in its content arrangement to make the theory and technical methods more practical in directing practitioners. This book introduces a series of core technologies with independent intellectual property rights. The self-developed and integrated prediction and evaluation system introduced in this book shows a wide range of application prospects in practice. It has important theoretical significance and practical promotion value for cultivating interdisciplinary talents who are proficient in geology, mathematics and information technology.
650 0 $a Metallogenic provinces $x Data processing. $3 3803786
650 1 4 $a Geology. $3 516570
650 2 4 $a Mineralogy. $3 516743
650 2 4 $a Mathematics of Planet Earth. $3 3236712
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-95-1770-1
950 $a Earth and Environmental Science (SpringerNature-11646)