Harmonic by harmonic removal technique for improving vibroseis data quality

In this paper, an improved method is presented to reduce vibrator harmonic distortion, one harmonic at a time and the method is illustrated with both simulated and field data. This method improves on the previous method that treated all the harmonics at once. The significant contribution in this procedure is a considerable reduction for the harmonics without any alteration for the weakest signals possibly present in positive and negative times. The core of the proposed technique depends on an accurate simulation for all the harmonics one by one existing in the positive and negative times of the data after cross‐correlation with the fundamental sweep and then subtracting the simulated harmonics from the original data using an optimization procedure. The steps and mathematical equations of the procedure are explained in detail in the body of the article in the section titled ‘harmonic by harmonic attenuation procedure’. Accordingly, a well‐developed procedure for enhancing the vibroseis data quality in both down‐ and up‐sweep data is illustrated. The procedure was tested on both synthetic and field data sets.     

Adsorption of BTEX on Surfactant Modified Granulated Natural Zeolite Nanoparticles: Parameters Optimizing by Applying Taguchi Experimental Design Method

In this paper, a novel adsorbent developed by means of granulating of natural zeolite nanoparticles (i.e., clinoptilolite) was evaluated for possible removal of the petroleum monoaromatics (i.e., benzene, toluene, ethylbenzene, and xylene, BTEX). To do this, the natural zeolite was ground to produce nanosized particulate, then modified by two cationic surfactants and granulated. The effect of various parameters including temperature, initial pH of the solution, total dissolved solids (TDS), and concentration of a competitive substance (i.e., methyl tert‐butyl ether, MTBE) were studied and optimized using a Taguchi statistical approach. The results ascertained that initial pH of the solution was the most effective parameter. However, the low pH (acidic) was favorable for BTEX adsorption onto the developed adsorbents. In this study, the experimental parameters were optimized and the best adsorption condition by determination of effective factors was chosen. Based on the S/N ratio, the optimized conditions for BTEX removal were temperature of 40°C, initial pH of 3, TDS of 0 mg/L, and MTBE concentration of 100 µg/L. At the optimized conditions, the uptake of each BTEX compounds reached to more than 1.5 mg/g of adsorbents.     

Effect of geological conditions on road construction in Jandagh Playa of Iran

The Jandagh–Moalleman road, which crosses the Great Kavir of Iran, was completed in 1999. Less than 1 year after completion, road subsidence problems began. In order to determine the causes of failure, field observations were taken along with surface and subsurface samples from road segments exhibiting typical problems. Laboratory experiments were conducted to determine their physical, chemical, and engineering properties. The results indicate that there are two typical layers in this playa: an upper, hard, salty crust layer composed of up to 46% soluble materials; and a lower, thick, muddy layer which is mostly composed of silt, clay minerals, gypsum, and halite. It was concluded that mineral dissolution of the upper salt crust layer and the sinking of road fill materials into the lower muddy layer, are the main causes of road settlement. An appropriate method to protect the road against the dissolution of its soluble materials is recommended.     

Arsenic in shallow groundwater of Bangladesh: investigations from three different physiographic settings

Occurrences of arsenic (As) in the Bengal Basin of Bangladesh show close relationships with depositional environments and sediment textures. Hydrochemical data from three sites with varying physiography and sedimentation history show marked variations in redox status and dissolved As concentrations. Arsenic concentration in groundwater of the Ganges Flood Plain (GFP) is characteristically low, where high Mn concentrations indicate redox buffering by reduction of Mn(IV)-oxyhydroxides. Low DOC, \( {\text{HCO}}^{ - }_{3} \), \( {\text{NH}}^{ + }_{4} \) and high \( {\text{NO}}^{ - }_{3} \) and \( {\text{SO}}^{{2 - }}_{4} \) concentrations reflect an elevated redox status in GFP aquifers. In contrast, As concentration in the Ganges Delta Plain (GDP) is very high along with high Fe and low Mn. In the Meghna Flood Plain (MFP), moderate to high As and Fe concentrations and low Mn are detected. Degradation of organic matter probably drives redox reactions in the aquifers, particularly in MFP and GDP, thereby mobilising dissolved As. Speciation calculations indicate supersaturation with respect to siderite and vivianite in the groundwater samples at MFP and GDP, but groundwater in the GFP wells is generally supersaturated with respect to rhodochrosite. Values of log P_CO2 at MFP and GDP sites are generally higher than at the GFP site. This is consistent with Mn(IV)-redox buffering suggested at the GFP site compared to Fe(III)-redox buffering at MFP and GDP sites.     

Open cluster membership probability based on K-means clustering algorithm

In the field of galaxies images, the relative coordinate positions of each star with respect to all the other stars are adapted. Therefore the membership of star cluster will be adapted by two basic criterions, one for geometric membership and other for physical (photometric) membership. So in this paper, we presented a new method for the determination of open cluster membership based on K-means clustering algorithm. This algorithm allows us to efficiently discriminate the cluster membership from the field stars. To validate the method we applied it on NGC 188 and NGC 2266, membership stars in these clusters have been obtained. The color-magnitude diagram of the membership stars is significantly clearer and shows a well-defined main sequence and a red giant branch in NGC 188, which allows us to better constrain the cluster members and estimate their physical parameters. The membership probabilities have been calculated and compared to those obtained by the other methods. The results show that the K-means clustering algorithm can effectively select probable member stars in space without any assumption about the spatial distribution of stars in cluster or field. The similarity of our results is in a good agreement with results derived by previous works.     

Gradient-based Pareto optimal history matching for noisy data of multiple types

The advantages of the simultaneous integration of production and time-lapse seismic data for history matching have been demonstrated in a number of previous studies. Production data provide accurate observations at particular spatial locations (wells), while seismic data enable global, though filtered/noisy, estimates of state variables. In this work, we present an efficient computational tool for bi-objective history matching, in which data misfits for both production and seismic measurements are minimized using an adjoint-gradient approach. This enables us to obtain a set of Pareto optimal solutions defining the optimal trade-off between production and seismic data misfits (which are, to some extent, conflicting). The impact of noise structure and noise level on Pareto optimal solutions is investigated in detail. We discuss the existence of the “best” trade-off solution, or least-conflicting posterior model, which corresponds to the history-matched model that is expected to provide the least-conflicting forecast of future reservoir performance. The overall framework is successfully applied in 2D and 3D compositional simulation problems to provide a single least-conflicting posterior model and, for the 2D case, multiple samples from the posterior distribution using the randomized maximum likelihood method.     

On the potential of Bartlett Lewis rectangular pulse models for simulating rainfall in Peninsular Malaysia

Abstract

The applicability of two versions of the Bartlett Lewis rectangular pulse model, the original and the modified model, is discussed for describing the temporal and spatial variation of rainfall patterns observed at 15 raingauge stations in Peninsular Malaysia over the period 1971–2008; 17 different sets of moment combinations are fitted to these models based on the generalized method of moments approach. The common statistics included in all sets are the mean, variance, lag-1 autocorrelation and the probability of dry based on the hourly rainfall data. The analysis was carried out on hourly rainfall data from all 15 stations for all months of the year. Two stations, Petaling Jaya and Kemaman, located on the west and east coasts of the Peninsula, respectively, are considered for illustration of the results, taking the months of July and November, which correspond to the driest and wettest months, corresponding to the southwest monsoon (May–August) and northeast monsoon (November–February), respectively. The best moment combination found for the illustrative results is based on the common statistics, as well as the mean and variance based on 24-h aggregated rainfall data, the inclusion of which successfully improved the model performance; the errors were significantly reduced. It was also found that the performance of the fitted models based on the mean absolute deviate error varies according to the type of Bartlett Lewis model applied: errors are much smaller for the fitted model based on the modified model as compared to the original model. In addition, the fitted statistics: mean, lag-1 autocorrelation and probability of dry are quite well fitted for several aggregated time scales; however, the variances are underestimated in both models for all aggregated time scales, particularly in the case of the original model. The results of extreme value analysis indicate that the modified model failed to reproduce the annual hourly and daily rainfall extremes satisfactorily.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Hanaish, I.S., Ibrahim, K., and Jemain, A.A., 2013. On the potential of Bartlett Lewis rectangular pulse models for simulating rainfall in Peninsular Malaysia. Hydrological Sciences Journal, 58 (8), 1690–1703.     

Application of neural network and ANFIS model for earthquake occurrence in Iran

This study examined the spatial-temporal variations in seismicity parameters for the September 10^th, 2008 Qeshm earthquake in south Iran. To this aim, artificial neural networks and Adaptive Neural Fuzzy Inference System (ANFIS) were applied. The supervised Radial Basis Function (RBF) network and ANFIS model were implemented because they have shown the efficiency in classification and prediction problems. The eight seismicity parameters were calculated to analyze spatial and temporal seismicity pattern. The data preprocessing that included normalization and Principal Component Analysis (PCA) techniques was led before the data was fed into the RBF network and ANFIS model. Although the accuracy of RBF network and ANFIS model could be evaluated rather similar, the RBF exhibited a higher performance than the ANFIS for prediction of the epicenter area and time of occurrence of the 2008 Qeshm main shock. A proper training on the basis of RBF network and ANFIS model might adopt the physical understanding between seismic data and generate more effective results than conventional prediction approaches. The results of the present study indicated that the RBF neural networks and the ANFIS models could be suitable tools for accurate prediction of epicenteral area as well as time of occurrence of forthcoming strong earthquakes in active seismogenic areas.     

Effect of Ozone and Ozone/Fenton in the Advanced Oxidation Process on Biodegradable Characteristics of Semi‐aerobic Stabilized Leachate

This study investigated the effects of O₃ and O₃/H₂O₂/Fe²⁺ in the advanced oxidation processes (AOPs) on the biodegradable and soluble characteristics of semi‐aerobic stabilized solid waste leachate. The biodegradability (BOD₅/chemical oxygen demand, COD) ratio improved from 0.034 to 0.05 and 0.1 following O₃ and O₃/H₂O₂/Fe²⁺, respectively. Fractions of biodegradable COD_(bi) (24%), non‐biodegradable COD_(ubi) (76%), soluble COD_(s) (59%), biodegradable soluble COD_(bsi) (38%), non‐biodegradable soluble COD_(ubsi) (62%), and particulate COD (PCOD) (41%) in stabilized leachate were also investigated. The fraction of COD_(bi) increased to 28 and 36% after applying O₃ and O₃/AOPs, respectively. COD_(S) increased to 59% after O₃ and to 72% after O₃/AOPs, whereas COD_(bsi) increased to 38 and 51% after O₃ and O₃/AOPs, respectively. The removal efficiency of COD_(S) was obtained at 5% after O₃ alone and improved to 51% following ozone‐based AOPs, whereas the removal efficiency of PCOD improved from 25% after O₃ to 71% after ozone‐based AOPs.