Promising technology and equipment for exploration of gold-bearing manmade mineral deposits

Large-volume dumps and tailings ponds at gold placers in the territory of Russia hold gold at the content close to the commercially attractive value. In the meanwhile, the amount of gold in profitable cut-off is steadily decreasing. In connection with this, it is important to commence extraction of gold from gold-bearing mining and processing waste. Alongside with commercial production interest, recycling of gold-bearing manmade raw material can help meet some environmental challenges. As against the detailed and operational exploration of natural gold deposits, exploration of mining and processing waste requires a nontrivial approach as waste contains difficult gold, including dispersed and chemically bonded particles, which requires an in-depth study into the substance and structure of such gold at micro and nano scale. Recycling of manmade mineral raw material in many cases assumes extraction of gold from it at the site of its storage. Accordingly, development of such waste needs innovative physicochemical geotechnologies, and exploration should involve assessment of quality characteristics and leaching resistance of the material. The authors propose new methods of sampling in prospecting headings inside mining and processing waste bodies. Exploration drilling should include local interval washout for representative sampling required for the mineralogical and chemical analyses, as well as for testing. To study formation of a reagent medium in pore solutions of manmade mineral raw material and to examine dissolved gold flow in the reagent medium, a new method is proposed for the mining waste exploration with arrangement of a system of additional umbrella sprinklers and catchers of test and pregnant solutions inside the body of waste mass, with feed via larger diameter holes.

Performance Index of Incremental Granular Model with Information Granule of Linguistic Intervals and Its Application

This paper addresses the performance index (PI) of an incremental granular model (IGM) with information granules of linguistic intervals. For this purpose, IGM is designed by combining a linear regression (LR) and an interval-based granular model (GM). The fundamental scheme of IGM construction comprises two essential phases: (1) development of LR as a basic model and (2) design of a local granular model, which attempts to reduce errors obtained by the LR model. Here, the local interval-based GM is based on an interval-based fuzzy clustering algorithm, which is materialized by information granulations. The PI of IGM is calculated by multiplying the coverage with specificity property, because the output of IGM is not a numerical value but a linguistic interval value. From the concept of coverage and specificity, we can construct information granules; thus, it is justified by the available experimental proof and presented as clearly defined semantics. To validate the PI method, an experiment is conducted on concrete compressive strength for civil engineering applications. The experimental results confirm that the PI of IGM is an effective performance evaluation method.

CRP-based seismic migration velocity analysis

A new migration velocity analysis is developed by combining the speed of parsimonious prestack depth migration with velocity adjustments estimated within and across common-reflection-point (CRP) gathers. The proposed approach is much more efficient than conventional tomographic velocity analysis because only the traces that contribute to a series of CRP gathers are depth migrated at each iteration. The local interval-velocity adjustments for each CRP are obtained by maximizing the stack amplitude over the predicted (nonhyperbolic) moveout in each CRP gather; this does not involve retracing rays. At every iteration, the velocity in each pixel is updated by averaging over all the predicted velocity updates. Finally, CRP positions and orientations are updated by parsimonious migration, and rays are retraced to define new CRP gathers for the next iteration; this ensures internal consistency between the updated velocity model and the CRP gather. Because the algorithm has a gridded-model parameterization, no explicit representation or fitting of reflectors is involved. Strong lateral-velocity variations, such as those found at salt flanks, can be handled. Application to synthetic and field data sets show that the proposed algorithm works effectively and efficiently.

Estimating anisotropy parameters and traveltimes in the τ‐p domain

The presence of anisotropy influences many aspects of seismic wave propagation and has therefore implications for conventional processing schemes. To estimate the anisotropy, we need both forward modelling and inversion tools. Exact forward modelling in anisotropic media is generally done by raytracing. However, we present a new and fast method, using the τ‐p transform, to calculate exact P and SV reflection moveout curves in stratified, laterally homogeneous, anisotropic media which requires no ray tracing. Results are exact even if the SV‐waves display cusps. In addition, we show how the same method can be used for parameter estimation. Since inversion for anisotropic parameters is very nonunique, we develop expressions requiring only a reduced number of parameters. Nevertheless, predictions using these expressions are more accurate than Taylor series expansions and are also able to handle cusps in the SV traveltime curves. In addition, layer stripping is a linear process. Therefore, both effective (average) and local (interval) estimates can be obtained.