Continuous wavelet transforms of spectral decomposition analyses for fluvial reservoir characterization of Miano Gas Field,Indus Platform,Pakistan

Fluvial depositional systems constitute diverse host for the hydrocarbons all over the globe. Nevertheless, predicting the hydrocarbon sands within these assorted sand systems is a challenge for the prospect generation. We apply the continuous wavelet transform of spectral decomposition technique to a 3D seismic data of the Miano Gas Field in the Indus Platform, Pakistan. Full spectrum seismic attributes like the amplitude and root mean square (RMS) detect the reservoir sands down to a restricted reservoir compartment. Nonetheless, the continuous wavelet transforms can be advantageous in imaging and enactment of these clastic reservoirs within the whole reservoir zone. Rock physics reveal high-quality reservoir with an average porosity ～25% together with the discrimination of lithology/fluids, signifying the bright chances for ascertaining the potential stratigraphic reservoirs.     

Fishery stock assessment of Kiddi shrimp (Parapenaeopsis stylifera) in the Northern Arabian Sea Coast of Pakistan by using surplus production models

Pakistani marine waters are under an open access regime.Due to poor management and policy implications,blind fishing is continued which may result in ecological as well as economic losses.Thus,it is of utmost importance to estimate fishery resources before harvesting.In this study,catch and effort data,1996-2009,of Kiddi shrimp Parapenaeopsis stylifera fishery from Pakistani marine waters was analyzed by using specialized fishery software in order to know fishery stock status of this commercially important shrimp.Maximum,minimum and average capture production of P.stylifera was observed as 15 912 metric tons(mt)(1997),9 438 mt(2009) and 11 667 mt/a.Two stock assessment tools viz.CEDA(catch and effort data analysis) and ASPIC(a stock production model incorporating covariates) were used to compute MSY(maximum sustainable yield) of this organism.In CEDA,three surplus production models,Fox,Schaefer and Pella-Tomlinson,along with three error assumptions,log,log normal and gamma,were used.For initial proportion(IP) 0.8,the Fox model computed MSY as 6 858 mt(CV=0.204,R~2=0.709) and 7 384 mt(CV=0.149,R~2=0.72) for log and log normal error assumption respectively.Here,gamma error produced minimization failure.Estimated MSY by using Schaefer and Pella-Tomlinson models remained the same for log,log normal and gamma error assumptions i.e.7 083 mt,8 209 mt and 7 242 mt correspondingly.The Schafer results showed highest goodness of fit R~2(0.712) values.ASPIC computed MSY,CV,R~2,F_(MSY)and B_(MSY) parameters for the Fox model as 7 219 mt,0.142,0.872,0.111 and 65 280,while for the Logistic model the computed values remained 7 720 mt,0.148,0.868,0.107 and 72 110 correspondingly.Results obtained have shown that P.stylifera has been overexploited.Immediate steps are needed to conserve this fishery resource for the future and research on other species of commercial importance is urgently needed.     

Interactions of copper, organic acids, and sulfate in goethite suspensions

Sorption of copper and sulfate onto goethite (-FeOOH) in aqueous solution is examined in Cu---SO₄ binary-sorbate systems and in Cu-SO₄-organic acid (either phthalic acid or chelidamic acid) ternary-sorbate systems. Compared to single-sorbate systems, sorption of Cu onto goethite was enhanced at low pH values in the presence of sulfate. Sorption data for Cu and SO₄ in Cu---SO₄ binary-sorbate systems were described with the Generalized Two Layer Model by proposing formation of a Cu---SO₄ ternary surface complex. Addition of sulfate to a Cu-phthalic acid binary sorbate system had little effect on Cu sorption. However, addition of sulfate to Cu-chelidamic acid binary-sorbate systems resulted in significant reduction of Cu sorption at low pH values, primarily due to competition for surface sites between sulfate and Cu-chelidamic acid ternary surface complexes. While organic acids such as humic substances can potentially influence sorption of metal ions, results from this study suggest that the extent of such influence may be strongly dependent on the presence of other sorbing anions, such as sulfate. Sorption of Cu and SO₄ in Cu---SO₄-organic acid ternary-sorbate systems was predicted reasonably well, based on surface reactions and equilibrium constants derived from fitting of sorption data from single- and binary-sorbate systems. These modeling results provide a validation of the extrapolation of sorption from simple systems to multicomponent systems through surface complexation modeling.     

数字摄影测量工作站DVP实验

用不同的采样间隔５０μｍ、７５μｍ与１００μｍ的数字形像，所量测之结果与解析测图仪ＢＣ２量测结果作了比较，得到了有益的结果，并概要地介绍了ＤＶＰ之功能与操作。     

Coupled physicochemical and bacterial reduction mechanisms for passive remediation of sulfate- and metal-rich acid mine drainage

Treatment of acid mine drainage (AMD) highly rich in sulfate and multiple metal elements has been investigated in a continuous flow column experiment using organic and inorganic reactive media. Treatment substrates that composed of spent mushroom compost (SMC), limestone, activated sludge and woodchips were incorporated into bacterial sulfate reduction (BSR) treatment for AMD. SMC greatly assisted the removals of sulfate and metals and acted as essential carbon source for sulfate-reducing bacteria (SRB). Alkalinity produced by dissolution of limestone and metabolism of SRB has provided acidity neutralization capacity for AMD where pH was maintained at neutral state, thus aiding the removal of sulfate. Fe, Pb, Cu, Zn and Al were effectively removed (87–100%); however, Mn was not successfully removed despite initial Mn reduction during early phase due to interference with Fe. The first half of the treatment was an essential phase for removal of most metals where contaminants were primarily removed by the BSR in addition to carbonate dissolution function. The importance of BSR in the presence of organic materials was also supported by metal fraction analysis that primary metal accumulation occurs mainly through metal adsorption onto the organic matter, e.g., as sulfides and onto Fe/Mn oxides surfaces.     

Porosity prediction of lower cretaceous unconventional resource play,south Indus Basin,Pakistan, using the seismic spectral decomposition technique

Incised-valley shale systems are renowned as the fruitful exploration domains. However, the stratigraphic heterogeneity is significant, and thus, identifying the porous compartments within the thin-bedded and fractured shale system is one of the unconventional stratigraphic challenges. We present an innovative scheme for the exploration of the porous unconventional resources within the south Indus basin, Pakistan. The continuous wavelet transforms (CWT) exclusively detects the porous shales within the complete fractured system as compared to the full spectrum seismic data interpretation tool. The seismic amplitude, instantaneous frequency, and reflection strength tools show some tuning effects due to lithology and fluids. However, the tuning block of 28 Hz envelope sub-bands in conjunction with instantaneous phase tool accurately mark out the shale-plugged pinch out reservoirs. The synthetic wedge model based on the conventional seismic wavelet resolves the shale bed (incised-valley shale-filled lens) of about 23 m thickness, but shows limited imaging capability due to frequency band limitation for the porous shale locale. The acoustic impedance based on instantaneous spectral porosity modeling using the tuning volume of 28 Hz CWT has spectacularly resolved the thin-beds (gas shows) within the porosity range of 20 to 30%, which may have implications for future exploration of unconventional stratigraphic plays.     

Geochemical assessment of Paleocene limestones of Sinn El-Kaddab Plateau,South Western Desert of Egypt,for industrial uses

The present work assesses the potential industrial uses of Paleocene limestone deposits, Garra Formation in Sinn El-Kaddab Plateau, South Western Desert of Egypt, based on their mineralogy and geochemical characteristics. Eighty-six limestone samples collected from ten stratigraphic columnar sections were analyzed using X-ray diffraction (XRD) and X-ray fluorescence (XRF) techniques. Petrographically, Garra limestone deposits consist dominantly of benthic foraminiferal wackestone and packstone microfacies. The XRD data revealed dominance of low-Mg calcite as essential carbonate mineral in the studied limestone. The bulk rock XRF results revealed CaO (29.28–55.75%) with an average of 52.74%. The CaO exhibits a strong negative correlation with MgO, SiO₂, TiO₂, Al₂O₃, and moderate negative correlation with Fe₂O₃ which indicates that the contribution of these elements is mainly due to detrital input. On the other hand, Al₂O₃ and Na₂O contents exhibit significant negative correlation with loss of ignition (LOI) wt% indicating their incorporation within terrigenous matrix. The average Sr content attains 1297 ppm indicating deposition in temperate marine environment. The average molar CaCO₃% values of bulk samples have been computed for individual columnar sections to determine the purity status of Garra limestone deposits. They range from impure (CaCO₃%?=?79.92%) to high-pure (CaCO₃%?=?97.76%) limestone. Therefore, Garra limestone deposits have extremely valuable uses in a wide spectrum of industrial applications including Portland cement, steel, ceramics, whiting, chemical uses, paper, and feed stuff.     

Assessing the impact of EI Niño southern oscillation index and land surface temperature fluctuations on dengue fever outbreaks using ARIMAX(<Emphasis Type="Italic">p</Emphasis>)-PARX(<Emphasis Type="Italic">p</Emphasis>)-NBARX(<Emphasis Type="Italic">p</Emphasis>) models

The dengue infectious disease remnants a human health problem in tropical and subtropical countries. In an Auto Regressive model to assess the role of climatic parameter El Niño Southern Oscillation and land surface mean monthly temperture on dengue outbreaks of the Karachi region over the monthly time interval January 2001 to December 2016, subsequent to stabilization of variance, we are able to apply and predict an Auto Regressive Integrated Moving Average Exogenous-Transfer Function model by using the order selection criteria namely Final Prediction Error and Akaike’s information. The results confirmed that ARIMAX (2,1,2) has fitted model, although an Auto Regressive model predicts a smaller decline in dengue data series than the auto Poisson Regression model. Additionally, we developed an alternative model for the Poisson Autoregressive Exogenous model in order (p) and Negative Binomial Auto Regressive Exogenous model, deliver the best fit as compared to the Poisson Auto Regressive Exogenous model whereas indicated by the deviances. The Pearson test showed a strong positive association between temperature and dengue, while ENSO inverse indication. High dengue outbreaks are detected in the months of September, October, and November. This comparative study exposed a significant relationship among monthly dengue and climatic variation by Auto Regressive Integrated Moving Average Exogenous (ARIMAX), Poisson and Negative-Binomial Autoregressive Exogenous (PARX-NBARX) models, while smallest values of AIC (3.89), Negative Binomial Auto Regressive Exogenous, are preferred more accurate model for the next 12 months forecasting. This study has provided useful information for the development of dengue predictions and future warning systems.     

Development of a flood forecasting system using IFAS: a case study of scarcely gauged Jhelum and Chenab river basins

Development of a well-calibrated, distributed hydrological model for flood forecasting based on rainfall and snowmelt is quite challenging, especially when in situ data is limited or unavailable. This paper presents the study carried out to parameterise the Integrated Flood Analysis System (IFAS) model for the trans-boundary, scarcely gauged catchments of Jhelum and Chenab rivers in Pakistan. Rainfall-runoff analysis was performed with a two-layered tank configuration, integrating snowmelt and dam and barrage operation from the very upstream in India to Trimmu Barrage in Pakistan. A grid size of 5?×?5 km was considered. Global map topography, land cover and soil data was utilised. The model was tested considering different magnitudes of floods of the years 2014, 2015 and 2017. The results showed that the satellite rainfall product, i.e. Global Satellite Mapping of Precipitation (GSMaP-NRT), underestimated the rainfall volume, compared to the ground-gauged rainfall. The GSMaP-IF correction method showed poor performance owing to the lack of ground observatory rainfall data for correcting the trans-boundary part of the basin. The GSMaP-Type1 correction method showed good results, except for the confluence point where complex flow conditions were not properly reproduced by the model. In addition, the incorporation of dam and barrages in the model improved the simulated flow results. It is concluded that the satellite rainfall estimates must be corrected to improve the results. Snowmelt module estimated the snowmelt contribution as 3 to 7% and 4 to 23% of the average daily discharge during the monsoon season at Mangla Dam and Marala Barrage, respectively, during 2014 and 2015. This study assessed various correction methods and concluded that the model and methodology used in the study functioned well with suitable precipitation.