Potential of legacy 2D seismic data for deep targeting and structural imaging at the Neves–Corvo massive sulphide-bearing deposit,Portugal

Seismic methods are becoming an established choice for deep mineral exploration after being extensively tested and employed for the past two decades. To investigate whether the early European mineral-exploration datasets had potential for seismic imaging that was overlooked, we recovered a low-fold legacy seismic dataset from the Neves–Corvo mine site in the Iberian Pyrite Belt in southern Portugal. This dataset comprises six 4–6 km long profiles acquired in 1996 for deep targeting. Using today's industry-scale processing algorithms, the world-class, ca. 150 Mt, Lombador massive sulphide and other smaller deposits were better imaged. Additionally, we also reveal a number of shallow but steeply dipping reflections that were absent in the original processing results. This study highlights that legacy seismic data are valuable and should be revisited regularly to take advantage of new processing algorithms and the experiences gained from processing such data in hard-rock environments elsewhere. Remembering that an initial processing job in hard rock should always aim to first obtain an overall image of the subsurface and make reflections visible, and then subsequent goals of the workflow could be set to, for example understanding relative amplitude ratios. The imaging of the known mineralization implies that this survey could likely have been among one of the pioneer studies in the world that demonstrated the capability of directly imaging massive sulphide deposits using the seismic method.     

A bias-free geodetic boundary value problem approach to height datum unification

A geodetic boundary value problem (GBVP) approach has been formulated which can be used for solving the problem of height datum unification. The developed technique is applied to a test area in Southwest Finland with approximate size of 1.5° × 3° and the bias of the corresponding local height datum (local geoid) with respect to the geoid is computed. For this purpose the bias-free potential difference and gravity difference observations of the test area are used and the offset (bias) of the height datum, i.e., Finnish Height Datum 2000 (N2000) fixed to Normaal Amsterdams Peil (NAP) as origin point, with respect to the geoid is computed. The results of this computation show that potential of the origin point of N2000, i.e., NAP, is (62636857.68 ± 0.5) (m²/s²) and as such is (0.191 ± 0.003) (m) under the geoid defined by W ₀ = 62636855.8 (m²/s²). As the validity test of our methodology, the test area is divided into two parts and the corresponding potential difference and gravity difference observations are introduced into our GBVP separately and the bias of height datums of the two parts are computed with respect to the geoid. Obtaining approximately the same bias values for the height datums of the two parts being part of one height datum with one origin point proves the validity of our approach. Besides, the latter test shows the capability of our methodology for patch-wise application.     

Prediction of Seaward Slope Recession in Berm Breakwaters Using M5' Machine Learning Approach

In the design process of berm breakwaters, their front slope recession has an inevitable rule in large number of model tests, and this parameter being studied. This research draws its data from Moghim’s and Shekari’s experiment results. These experiments consist of two different 2D model tests in two wave flumes, in which the berm recession to different sea state and structural parameters have been studied. Irregular waves with a JONSWAP spectrum were used in both test series. A total of 412 test results were used to cover the impact of sea state conditions such as wave height, wave period, storm duration and water depth at the toe of the structure, and structural parameters such as berm elevation from still water level, berm width and stone diameter on berm recession parameters. In this paper, a new set of equations for berm recession is derived using the M5'' model tree as a machine learning approach. A comparison is made between the estimations by the new formula and the formulae recently given by other researchers to show the preference of new M5'' approach.     

Prediction of the median IDA curve by employing a limited number of ground motion records

A methodology has been proposed which can be used to reduce the number of ground motion records needed for the reliable prediction of the median seismic response of structures by means of incremental dynamic analysis (IDA). This methodology is presently limited to predictions of the median IDA curve only. The reduction in the number of ground motion records needed to predict the median IDA curve is achieved by introducing a precedence list of ground motion records. The determination of such a list is an optimization problem, which is solved in the paper by means of (1) a genetic algorithm and (2) a proposed simple procedure. The seismic response of a simple, computationally non‐demanding structural model has been used as input data for the optimization problem. The presented example is a three‐storey‐reinforced concrete building, subjected to two sets of ground motion records, one a free‐field set and the other a near‐field set. It is shown that the median IDA curves can be predicted with acceptable accuracy by employing only four ground motion records instead of the 24 or 30 records, which are the total number of ground motion records for the free‐field and near‐field sets, respectively. Copyright © 2007 John Wiley & Sons, Ltd.     

Strong ground motion from the November 12, 2017, <Emphasis Type="Bold">M</Emphasis> 7.3 Kermanshah earthquake in western Iran

In this paper, we analyzed the strong ground motion from the November 12, 2017, Kermanshah earthquake in western Iran with moment magnitude (M) of 7.3. Nonlinear and linear amplification of ground motion amplitudes were observed at stations with soft soil condition at hypocentral distances below and above 100 km, respectively. Observation of large ground motion amplitudes dominated with long-period pulses on the strike-normal component of the velocity time series suggests a right-lateral component of movement and propagation of rupture towards southeast. Comparison of the horizontal peak ground acceleration (PGA) from the M 7.3 earthquake with global PGA values showed a similar decay in ground motion amplitudes, although it seems that PGA from the M 7.3 Kermanshah earthquake is higher than global values for NEHRP site class B. We also found that the bracketed duration (D_b) was higher in the velocity domain than in the acceleration domain for the same modified Mercalli intensity (MMI) threshold. For example, D_b reached ~?30 s at the maximum PGA while it was ~?50 s at the maximum peak ground velocity above the threshold of MMI?=?5. Although the standard design spectrum from Iranian Code of Practice for Seismic Resistant Design of Buildings (standard No. 2800) seems to include appropriate values for the design of structures with fundamental period of 1 s and higher, it is underestimated for near-field ground motions at lower periods.     

A coarse-scale compositional model

In subsurface flow modeling, compositional simulation is often required to model complex recovery processes, such as gas/CO ₂ injection. However, compositional simulation on fine-scale geological models is still computationally expensive and even prohibitive. Most existing upscaling techniques focus on black-oil models. In this paper, we present a general framework to upscale two-phase multicomponent flow in compositional simulation. Unlike previous studies, our approach explicitly considers the upscaling of flow and thermodynamics. In the flow part, we introduce a new set of upscaled flow functions that account for the effects of compressibility. This is often ignored in the upscaling of black-oil models. In the upscaling of thermodynamics, we show that the oil and gas phases within a coarse block are not at chemical equilibrium. This non-equilibrium behavior is modeled by upscaled thermodynamic functions, which measure the difference between component fugacities among the oil and gas phases. We apply the approach to various gas injection problems with different compositional features, permeability heterogeneity, and coarsening ratios. It is shown that the proposed method accurately reproduces the averaged fine-scale solutions, such as component overall compositions, gas saturation, and density solutions in the compositional flow.