Simulation of mineral grades and classification of mineral resources by using hard and soft conditioning data: application to Sungun porphyry copper deposit

The presence of geological units with different grade characteristics mostly leads to problems during the grade modeling process. In special cases, if the area under study has units with small thickness and low grade with respect to the dominant unit of the area, it is difficult to reproduce different grade contents in these units in the simulated grade models because of the low thickness and lack of data in these units. In this study, the local moment constraints method, based on the definition of soft conditioning data reflecting geological knowledge, is investigated for improving simulated grade models under the mentioned conditions. This method is applied for grade simulation at the 1,750 m level of Sungun porphyry copper mine. The studied area is divided into two rock type domains: Sungun porphyry and Dyke. The Sungun porphyry unit is the dominant rock type in the considered area and has, on average, a higher copper grade, while dykes discontinue Sungun porphyry rock units sporadically and most of them are barren of mineralization. It is demonstrated that the use of soft conditioning data makes the simulated grade model closer to reality and improves the reproduction of grade contents considering the rock type units in the area. In the next step, the results obtained from conditional simulation are used for mineral resources classification. To this end, the conditional coefficient of variation is chosen as a criterion for measuring uncertainty and for defining the resources classes. Then, it is shown that uncertainty can be considerably reduced in the prepared models if soft data are considered; as a result, an increase in measured resource classification is observed.     

Ensemble Spatial Interpolation: A New Approach to Natural or Anthropogenic Variable Assessment

Natural Resources Research - This paper presents a novel and versatile framework for building ensemble spatial interpolation functions. As with all ensemble methods, the central idea is to assemble...     

The Persian Gulf Basin: Geological history, sedimentary formations, and petroleum potential

The Persian Gulf Basin is the richest region of the World in terms of hydrocarbon resources. According to different estimates, the basin contains 55–68% of recoverable oil reserves and more than 40% of gas reserves. The basin is located at the junction of the Arabian Shield and Iranian continental block that belong to two different (Arabian and Eurasian) lithospheric plates. Collision of these plates at the Mesozoic/Cenozoic boundary produced the Zagros Fold Belt and the large Mesopotamian Foredeep, which is a member of the Persian Gulf Basin. During the most part of the Phanerozoic, this basin belonged to an ancient passive margin of Gondwana, which was opened toward the Paleotethys Ocean in the Paleozoic and toward the Neotethys in the Mesozoic. Stable subsidence and the unique landscape-climatic conditions favored the accumulation of a very thick sedimentary lens of carbonate rocks and evaporites (up to 12–13 km and more). Carbonate rocks with excellent reservoir properties are widespread, while the evaporites play the role of regional fluid seals. Organicrich rocks, which can generate liquid and gaseous hydrocarbons (HC), are present at different levels in the rock sequence.     

Application of Convergence–Confinement Method in Analysis of Shallow Non-circular Tunnels

Stress reduction factor, λ, is a dimensionless coefficient in two-dimensional (2D) analysis based on convergence confinement method (CCM) of tunnel which represents stress relaxation in the tunnel walls at different excavation steps. The aim of this paper is to look into the influencing factors on parameter λ around the tunnel walls using finite difference code in order to improve the accuracy of the CCM. For this purpose, four different ground types with various tunnel radii, depths and cross section shapes are considered. Finally, the 2D analysis using uniform and variable stress reduction factors determined in this paper is compared with the 3D analysis of the tunnel. The results of this study enhance our understanding of the role of geometrical and soil material parameters of tunnel on stress relaxation around tunnel walls. The tunnel depth, soil type and tunnel shape have great influence on λ. Variable stress reduction factor enables the convergence–confinement method to predict the realistic behavior of third dimension of the tunnel and can also be used as the best alternative to 3D models.     

Analogue modeling of the role of multi-level decollement layers on the geometry of orogenic wedge: an application to the Zagros Fold–Thrust Belt,SW Iran

International Journal of Earth Sciences - The presence of evaporate and incompetent formations (i.e., decollement horizons) within the sedimentary sequence of fold-thrust belts can control their...     

Ductile steel plate external end diaphragms for steel tub girder straight highway bridges

The end diaphragm of bridges are normally designed to resist lateral seismic forces imposed on the superstructure in earthquake prone regions. Using ductile diaphragms with high deformation capacity could reduce the seismic demands on the substructure and prevent costly damage under strong ground motions. The end diaphragms of steel tub girder bridges with high lateral stiffness and dominant shear behavior have a potential to be used as ductile fuse elements. In this study, a steel plate shear diaphragm(SPSD) is introduced as an external end diaphragm of tub girder steel bridges to reduce the seismic demands imposed on the substructure. Quasi static nonlinear analyses were conducted to evaluate responses of sixteen SPSDs with different boundary conditions, aspect ratios and diaphragm plate thicknesses. Moreover, nonlinear time history analyses were performed using three different ground motions corresponding to DBE and MCE level spectrums. Cyclic and time history analyses proved the proper behavior of SPSD and its efficiency to reduce seismic demands by more than 25%.     

Predicting seismic permanent displacement of soil walls under surcharge based on limit analysis approach

Seismic permanent displacement of the soil walls plays an important role in design of these structures. Due to the increase in growth of urban areas and the limitations in use of flat grounds, many structures are built near slopes and retaining walls. During earthquakes, these structures can apply an additional surcharge on the wall. The intensity and location of the surcharge is of considerable importance on the seismic displacements of the soil wall. In this study, by using the limit analysis and upper bound theorem, seismic permanent displacement of the soil wall under surcharge has been analyzed. Thus, a formulation is presented for calculating the yield acceleration and seismic displacement for different surcharge conditions. The effect of seismic acceleration, surcharge intensity, its location and soil properties is investigated. A parameter called the “displacement coefficient” is proposed, and is a potential modification for Newmark’s sliding-block method.     

Quantitative integration of 3D and 4D seismic impedance into reservoir simulation model updating in the Norne Field

The ultimate goal of reservoir simulation in reservoir surveillance technology is to estimate long-term production forecasting and to plan development and management of petroleum fields. However, maintaining reliable reservoir models which honour available static and dynamic data, involve inherent risks due to the uncertainties in space and time of the distribution of hydrocarbons inside reservoirs. Recent applications have shown that these uncertainties can be reduced by quantitative integration of seismic data into the reservoir modelling workflows to identify which areas and reservoir attributes of the model should be updated. This work aims using seismic data to reduce ambiguity in calibrating reservoir flow simulation model with an uncertain petro-elastic model, proposing a circular workflow of inverted seismic impedance (3D and 4D) and engineering studies, with emphasis on the interface between static and dynamic models. The main contribution is to develop an updating procedure for adjusting reservoir simulation response before using it in the production forecasting and enhance the interpretive capability of reservoir properties. Accordingly, the workflow evaluates consistency of reservoir simulation model and inverted seismic impedance, assisted by production history data, to close the loop between reservoir engineering and seismic domains. The methodology is evaluated in a complex, faulted, sandstone reservoir, the Norne benchmark field, where a significant reservoir behaviour understanding (about the static and dynamic reservoir properties) is obtained towards the quantitative integration of seismic impedance data. This leads to diagnosis of the reservoir flow simulation reliability and generation of an updated simulation model consistent with observed seismic and well production history data, as well as a calibrated petro-elastic model. Furthermore, as Norne Field is a benchmark case, this study can be considered to enrich the discussions over deterministic or probabilistic history matching studies.     

Nonparametric Geostatistical Simulation of Subsurface Facies: Tools for Validating the Reproduction of,and Uncertainty in,Facies Geometry

Delineation of facies in the subsurface and quantification of uncertainty in their boundaries are significant steps in mineral resource evaluation and reservoir modeling, which impact downstream analyses of a mining or petroleum project. This paper investigates the ability of nonparametric geostatistical simulation algorithms (sequential indicator, single normal equation and filter-based simulation) to construct realizations that reproduce some expected statistical and spatial features, namely facies proportions, boundary regularity, contact relationships and spatial correlation structure, as well as the expected fluctuations of these features across the realizations. The investigation is held through a synthetic case study and a real case study, in which a pluri-Gaussian model is considered as the reference for comparing the simulation results. Sequential indicator simulation and single normal equation simulation based on over-restricted neighborhood implementations yield the poorest results, followed by filter-based simulation, whereas single normal equation simulation with a large neighborhood implementation provides results that are closest to the reference pluri-Gaussian model. However, some biases and inaccurate fluctuations in the realization statistics (facies proportions, indicator direct and cross-variograms) still arise, which can be explained by the use of a single finite-size training image to construct the realizations.