تلفیق داده‌های زمین‌شناسی و تصاویر ماهواره‌ای Sentinel-2A و ASTER برای اکتشاف ذخایر سرب و روی در ورقه سقز

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه زمین‌شناسی، دانشکده علوم زمین، دانشگاه شهید چمران اهواز، اهواز، ایران

2 گروه فتوگرامتری و سنجش از دور، دانشکده مهندسی ژئودزی و ژئوماتیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

3 گروه زمین‌شناسی، دانشکده علوم، دانشگاه تهران، تهران، ایران

چکیده

مقدمه
مدل‌سازی پتانسیل معدنی براساس جمع‌آوری و پردازش دقیق داده‌های زمین‌شناسی، زمین‌فیزیکی و ماهواره‌ای، این امکان را فراهم می­کند تا پتانسیل وجود ماده معدنی در یک منطقه خاص را پیش‌بینی کنیم. این فرآیند شامل ساخت مدل‌های ریاضی پیچیده است که با استفاده از الگوریتم‌های یادگیری ماشین و تجزیه و تحلیل دقیق داده‌ها، به به مسئولان و تصمیم‌گیران در زمینه استخراج معدنی کمک می‌کنند تا مناطق مستعد کانه­زایی برای بهره‌برداری بهینه را تعیین کنند و منابع زمین را به بهترین شکل مدیریت کنند. با توجه به واحدهای زمین­شناسی متنوع موجود در ورقه سقز این ورقه یکی از با پتانسیل­ترین مناطق برای تشکیل ذخایر فلزی می­باشد. سنگ میزبان اکثر کانسارهای سرب و روی موجود در ایران رسوبی می­باشد که با عنوان کانسارهای سرب و روی با سنگ میزبان رسوبی (Sedimentary-Hosted) شناخته می­شوند. طبق بررسی­های صورت گرفته نیز مشخص شد کانه­زایی سرب و روی صورت گرفته در ورقه یکصدهزار سقر نیز از این نوع ­می­باشد که عموماً کلسیت، دولومیت، شیل، ماسه­سنگ و سنگ­های آذرآواری میزبان این ذخایر می­باشند.
مواد و روش­ها
در این پژوهش از لایه­های اکتشافی لیتولوژی، دگرسانی دولومیتی، ژئوشیمی سرب و روی برای تهیه نقشه پیش­بینی کانه­زایی سرب و روی در ورقه سقز استفاده شد. بهره­گیری از تکنیک سینگولاریتی بر روی رسوبات آبراهه­ای سرب و روی، استفاده از لایه­های اکتشافی متنوع و انجام طیف­سنجی آزمایشگاهی و اعمال منحنی­های رفتار طیفی به دست آمده بر روی تصاویر Sentinel-2A در این پژوهش نوآوری و خلاقانه بودن آن را نسبت به سایر پژوهش­های مشابه نشان می­دهد. پس از فازی­سازی لایه­های اکتشافی در نرم­افزار GIS نقشه پیش­بینی کانه­زایی سرب و روی توسط تابع Fuzzy-Gamma و مقدار گامای 85/0 بدست آمد. نتایج حاصل از تجزیه XRF و ICP-MS بر روی نمونه­های سرب و روی کشف­شده عیار بین 3 تا 7% را نشان داد که بیانگر انتخاب درست منطقه مورد مطالعه و لایه­های اکتشافی و تلفیق صحیح آن­ها می­باشد. در ادامه با انجام طیف سنجی آزمایشگاهی در اتاق تاریک با لامپ هالوژن و دستیابی به منحنی رفتار طیفی کانی اسفالریت مربوط به نمونه­های منطقه مورد مطالعه، الگوریتم تطابق سنجی SAM روی تصاویر ماهواره­­ای Sentinel-2A، اعمال شد.
نتایج و بحث
طبق پی­جویی­های صورت گرفته در 6 محدوده S1، S2، P، Q-Pb-Zn، Polygon12 و Polygon13 نمونه­های حاوی کانه­زایی سرب و روی کشف شد و فقط محدوده Polygon5 فاقد کانه­زایی سرب و روی تشخیص داده شد که نشانگر قابل اعتماد بودن لایه­های اکتشافی و روش تلفیق می­باشد. نتایج آنالیز XRF وAqua Regia  نشان داد که نمونه­های حاوی سرب و روی کشف شده عیاری بین 2 تا 7 درصد داشته که مشخص کننده عیار اقتصادی برای این فلزات می­باشد.
نتیجه­گیری
نتایج حاصل از انجام طیف­سنجی آزمایشگاهی و اعمال منحنی­های رفتار طیفی کانی اسفالریت بر روی تصاویر ماهواره­ای Sentinel-2A به نوعی برای بررسی دقت کار و شناسایی نواحی امیدبخش معدنی جدید استفاده شد. با مقایسه طیف­های اصلاح­ شده بر روی تصاویر Sentinel-2A بدست آمده از آزمایشگاه با کتابخانه USGS مشخص شد رفتار طیفی بدست آمده مشابه کتابخانه طیفی USGS می­باشد لذا نقشه پیش­بینی کانه­زایی سرب و روی حاصل از اعمال منحنی رفتار طیفی اسفالریت بر روی تصاویر ماهواره­ای Sentinel-2A بیانگر روش درست انتخاب تصویر، طیف­سنجی مناسب و تمامی پردازش­ها می­باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Integration of geological data and Sentinel-2A and ASTER satellite images for the exploration of Pb-Zn deposits in the Saqez geological sheet

نویسندگان [English]

  • MohamadAmin Jafari 1
  • hamed kachar 2
  • ali zeinali 3
  • Alireza Zarasvandi 1
1 Department of Geology, Faculty of Earth Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2 Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K.N Toosi University of Technology, Tehran, Iran
3 Department of Geology, College of Science, University of Tehran, Tehran, Iran
چکیده [English]

Introduction
Modeling mineral potential based on the precise collection and processing of geological, geophysical, and satellite data enables us to predict the potential presence of mineral substances in a specific area. This process involves constructing complex mathematical models that, utilizing machine learning algorithms and thorough data analysis, assist authorities and decision-makers in the mining sector. It helps identify mineral-rich zones for optimal extraction and manage land resources in the best possible way. Given the diverse geological units present in the Saqez sheet, this sheet is considered one of the most promising areas for the formation of metallic deposits. The host rock for most Pb-Zn deposits in Iran is sedimentary, known as Sedimentary-Hosted Pb-Zn deposits. According to conducted surveys, it has been determined that the Pb-Zn mineralization occurring in the Saqez sheet is also of this type. Typically, calcite, dolomite, shale, sandstone, and igneous rocks serve as hosts for these deposits.
 
Materials and Methods
In this research, the exploratory layers of lithology, dolomite alteration, and geochemical of Pb-Zn were used to prepare a map of the prediction of Pb-Zn mineralization in the turpentine sheet. Utilizing the singularity technique on sediments stream, using various exploratory layers performing laboratory spectroscopy, and applying the spectral behavior curves obtained on Sentinel-2A images in this innovative and creative research. It shows its existence compared to another similar research. After fuzzification of exploration layers in GIS software, the prediction map of Pb-Zn mineralization was obtained by Fuzzy-Gamma function and gamma value of 0.85. The results of XRF and ICP-MS analysis on the discovered Pb-Zn samples showed a grade between 3 and 7%, which indicates the correct selection of the studied area and the exploratory layers and their correct integration. Further, by conducting laboratory spectroscopy in a dark room with a halogen lamp and obtaining the spectral behavior curve of the sphalerite mineral related to the samples of the study area, the SAM matching algorithm was applied to the Sentinel-2A satellite images.
Results and Discussion
According to the Pb-Zn mineralization prediction map of the Saqez sheet, this map is classified into four categories of low, moderate, high, and extreme mineralization potential. It is evident from this map that the northern, central, and southeastern regions have the highest potential for Pb-Zn mineralization. Upon examining the topography and road identification of the Saqez sheet, six areas were selected for exploratory drilling of Pb-Zn. Samples were collected for analysis and validation of identified points. XRF and ICP-MS analysis results indicated that the total Pb-Zn content ranged from 2 to 7% and 70,000 to 20,000 ppm. Finally, high-grade Pb-Zn samples were selected for petrographic examination. Petrographic studies revealed that minerals such as sphalerite, galena, and pyrite were predominant in the collected samples, with their texture filling the pore spaces. Specifically, sphalerite replaced galena, and galena replaced pyrite.
The results obtained from laboratory spectral analysis and the application of spectral behavior curves for sphalerite minerals on Sentinel-2A satellite images were utilized to assess the accuracy of the work and identify promising new mineralized areas. By comparing the corrected spectra from the laboratory experiments with the USGS spectral library, it was determined that the obtained spectral behavior is similar to the USGS spectral library. Therefore, the predictive map of Pb-Zn mineralization resulting from the application of spectral behavior curves for sphalerite on Sentinel-2A satellite images indicates the correct selection of imagery, appropriate spectral analysis, and all processing steps.
 
Conclusion
Due to the fact that the host rocks of most Pb-Zn deposits in Iran are of sedimentary origin, the first step in modeling the mineral potential of these deposits is to accurately recognize the ore deposit type. Based on the evidence and samples observed in the study area, the ore deposit type in the study area can be considered as the Irish type. Therefore, based on this, modeling and prediction of Pb-Zn mineralization on the one hundred thousand scale map of Saqez were carried out according to the Irish type Pb-Zn mineralization.
After evaluating the Pb-Zn mineral potential map, seven final areas were selected for exploration. Based on the exploration conducted in six areas (S1, S2, P, Q-Pb-Zn, Polygon12, and Polygon13), samples containing Pb-Zn mineralization were discovered, while Polygon5 was identified as lacking Pb-Zn mineralization, indicating the reliability of the exploration layers and integration method. XRF and Aqua Regia analysis results showed that the discovered Pb-Zn samples had grades ranging from two to seven percent, indicating economic-grade content for these metals.

کلیدواژه‌ها [English]

  • Pb-Zn exploration
  • Singularity
  • Spectroscopy
  • Sentinel-2A
  • Saqez

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