induced polarization
در نشریات گروه مهندسی معدن-
The properties of metallic minerals and metallic minerals-electrolyte interface have always been a concern in the induced polarization (IP) geophysical method due to their effects on the IP response. Electrochemical reactions, if carried out, affect the interface characteristics. Hence, the occurrence of the reactions and their effects on the IP signal have been modeled through recent research, but they are not well-known yet. Identifying these matters can help to create more realistic physical and petrophysical models, for a better explanation of IP effects. So, in the present study, 11 metallic mineral samples and the laboratory method named bipolar electrochemistry, introduced for the first time to the IP research field, have been used to show the performance of electrochemical reactions at the interface and the effect of various metallic minerals on them. The results showed that if the applied external electric potential is high enough, electrochemical reactions are carried out at the metallic minerals-electrolyte interface. In this study, these reactions were electrolysis of water and were carried out in all minerals (except sphalerite). However, the potential required to initiate the reactions was different for different minerals. The lack of water electrolysis reaction on the surface of sphalerite can probably be attributed to its non-conductivity. On the other hand, the external potential responsible for the interface reactions was linearly linked to the potential difference between the two sample’s extremities. Considering the different potentials required to start the reactions in various samples-electrolyte interfaces, and the absence of these reactions in the case of sphalerite samples, it can be concluded that the samples’ compounds affect the reactions and their commencing potentials. So, we believe that by studying these reactions, some properties of the metallic minerals can be achieved. Identifying the minerals’ properties and the reactions that can occur at their surfaces is essential for a detailed understanding of the factors affecting the IP phenomenon. To do this, we found bipolar electrochemistry as an appropriate way.
Keywords: Bipolar Electrochemistry, Induced polarization, Redox Reactions, Sulfide Minerals -
در پژوهش حاضر شبکه عصبی احتمالاتی مبتنی بر الگوریتم احتمالاتی بایزین برای طبقه بندی عیار کانسار مس علی آباد یزد بکار گرفته شد. برای این منظور از داده های ژیوفیزیکی قطبش القایی (IP) و مقاومت ویژه (Rs) و اطلاعات زمین شناسی نوع سنگ مغزه های حفاری گمانه های اکتشافی واقع بر روی چهار پروفیل ژیوفیزیکی به نام های DD-1 ، PD-2 ، PD-3 و PD-4 به- عنوان پارامترهای ورودی و پارامتر عیار مس گمانه ها به عنوان پارامتر هدف استفاده شد. برای دست یابی به مقصود بطور تصادفی تعداد 488، 528، 188 و 456 داده به ترتیب از مقاطع منطبق بر پروفیل های ژیوفیزیکی DD-1 ، PD-2 ، PD-3 و PD-4 برداشت شد که 75 درصد از کل داده ها برای یادگیری و 25 درصد برای ارزیابی عملکرد شبکه عصبی احتمالاتی انتخاب شد. عملکرد رویکرد پیشنهادی از طریق نسبت مجموع داده های روی قطر اصلی به کل داده های آزمون توسط ماتریس درهم آمیختگی و تعیین خطای کامیژن و آمیژن، مورد ارزیابی قرار گرفت. نتایج پژوهش نشان می دهند که شبکه عصبی احتمالاتی توانسته داده- های آزمون مربوط به پروفیل های DD-1 ، PD-2 ، PD-3 و PD-4 را به ترتیب با 60، 74، 60 و 3/83 درصد دقت برآورد نماید که با توجه به نوع داده های دردسترس، قابل قبول می باشند. همچنین نتایج از طریق ترسیم نقشه هم عیار چهار مقطع اکتشافی منطبق بر پروفیل های ژیوفیزیکی، به کمک داده های عیارسنجی گمانه های اکتشافی، شبکه بندی و درونیابی شبکه با استفاده از روش تخمین دقیق کریجینگ، بطور کیفی مورد ارزیابی قرار گرفت که نتایج مطلوبی حاصل شد.
کلید واژگان: کانسار مس علی آباد یزد، شبکه عصبی احتمالاتی بایزین، مقاومت ویژه و قطبش القایی، نوع سنگ، عیارIn the present research, a probabilistic neural network based on the Bayesian probabilistic algorithm was employed to classify the grade of Ali-Abad copper deposit in Yazd. For this purpose, induced polarization (IP) and resistivity (Rs) geophysical data and rock type of exploration borehole cores as geological information corresponding to four geophysical profiles, DD-1, PD-2, PD-3 and PD-4 were used as input parameters as well as the copper grade of the boreholes as target parameter. To achieve the goal, 488, 528, 188, and 456 data were randomly collected from the sections related to DD-1, PD-2, PD-3 and PD-4 geophysical profiles so that 75% of total data were selected for training and 25% to test the probabilistic neural network. The performance of the proposed approach was evaluated by confusion matrix through the ratio of summation of data on the main diameter to the total test data, as well as determination of Commission and Omission errors. The results of the research show that the probabilistic neural network could estimate the test data for DD-1, PD-2, PD-3 and PD-4 profiles with accuracy of 60, 74, 60 and 83.3%, respectively which are reasonable considering the type of available data. In addition, the results were qualitatively evaluated through plotting isograde maps of four exploratory cross-sections over the geophysical profiles. This process was carried out using the assay data of exploration boreholes, gridding and the grid interpolation with the high accurate kriging estimation method, which was leaded to favorite results.
Keywords: Yazd Ali-Abad copper deposit, Bayesian probabilistic neural network, Resistivity, Induced polarization, Rock Type, Grade -
Madan Bozorg is an active copper mine located in NE Iran, which is a part of the very wide copper mineralization zone named Miami-Sabzevar copper belt. The main goal of this research work is the 3D model construction of the induced polarization (IP) and resistivity (Rs) data with quantifying the uncertainties using geostatistical methods and drilling. Four profiles were designed and surveyed using the CRSP array based on the boreholes. The data obtained was processed, 2D sections of IP and Rs were prepared for each profile by inverting the data, and these sections were evaluated by some exploratory boreholes in the studied area. Based on the geostatistical methods, 3D block models were constructed for the 2D IP and Rs data, and the uncertainties in the prepared models were obtained. The mineralization location was determined according to the geophysical detected anomalies. In order to check the models, some locations were proposed for drilling in the cases that the borehole data was unavailable. The drilling results indicated a high correlation between the identified anomalies from the models and mineralization in the boreholes. The results obtained show that it is possible to construct 3D models from surveyed 2D IP & Rs data with an acceptable error level. In this way, the suggested omitted drilling locations were optimized so that more potentials could be obtained for copper exploration by the least number of boreholes.Keywords: 3D Model, Induced Polarization, Resistivity, Geostatistics, Uncertainties, Drilling
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