Spatiotemporal shoreline change in Boushehr Province coasts,Iran

Journal of Oceanology and Limnology - Since coastal areas have highly dynamic nature and are one of the most beneficial regions of civilizations, it is of great significance to understand their...     

Surface runoff prediction regarding LULC and climate dynamics using coupled LTM,optimized ARIMA,and GIS-based SCS-CN models in tropical region

The effects of climate and land use/land cover (LULC) dynamics have directly affected the surface runoff and flooding events. Hence, current study proposes a full-packaged model to monitor the changes in surface runoff in addition to forecast of the future surface runoff based on LULC and precipitation variations. On one hand, six different LULC classes were extracted from Spot-5 satellite image. Conjointly, land transformation model (LTM) was used to detect the LULC pixel changes from 2000 to 2010 as well as predict the 2020 ones. On the other hand, the time series-autoregressive integrated moving average (ARIMA) model was applied to forecast the amount of rainfall in 2020. The ARIMA parameters were calibrated and fitted by latest Taguchi method. To simulate the maximum probable surface runoff, distributed soil conservation service-curve number (SCS-CN) model was applied. The comparison results showed that firstly, deforestation and urbanization have been occurred upon the given time, and they are anticipated to increase as well. Secondly, the amount of rainfall has non-stationary declined since 2000 till 2015 and this trend is estimated to continue by 2020. Thirdly, due to damaging changes in LULC, the surface runoff has been also increased till 2010 and it is forecasted to gradually exceed by 2020. Generally, model calibrations and accuracy assessments have been indicated, using distributed-GIS-based SCS-CN model in combination with the LTM and ARIMA models are an efficient and reliable approach for detecting, monitoring, and forecasting surface runoff.     

Experimental Study on the Sand of Bandar-e Anzali Using Shaking Table

Geotechnical and Geological Engineering - Due to the economic and tourist importance of Bandar-e Anzali coastal zone and also the high seismic risk in this area, this article provides an...     

Quantitative pore-type characterization from well logs based on the seismic petrophysics in a carbonate reservoir

Quality, availability and consistency of the measured and interpreted well log data are essential in the seismic reservoir characterization methods, and seismic petrophysics is the recommended workflow to achieve data consistency between logs and seismic domains. This paper uses seismic petrophysics workflow to improve well logs and pore geometry interpretations for an oil carbonate reservoir in the Fahliyan Formation in the southwest of Iran. The petrophysical interpreted well logs, rock physics and well-to-seismic tie analysis are integrated into the proposed workflow. Our implementation incorporates revising petrophysical well log interpretations and updating pore geometry characteristics to obtain a better well-tie quality. We first propose an improved pore-type characterization approach based on both P- and S-wave velocities for quantifying pore geometry. Then, seismic logs are estimated accordingly, and the results are used in the well-to-seismic analysis. The quality of the well-tie is improved, furthermore, by iterating on the petrophysical interpreted well logs as well as the calculated pore geometries. For the intervals with high-quality data, our workflow improves the consistency between the results of measured and modelled seismic logs. For the intervals with problematic well logs, the application of our proposed workflow results in the successful replacement of the poor data and subsequently leads to an improved wavelet estimation and well-tie results. In both cases, a higher quantification of pore geometries is achieved, which in turn is confirmed by the core images and formation micro-imager analysis.     

Earth surface deformation analysis of 2005 Qeshm earthquake based on three-dimensional displacement field derived from radar imagery measurements

We derived the 3D vector displacement field due to the 5.9 Mw Qeshm island (Iran) earthquake using ascending and descending interferograms and azimuth offsets obtained from ENVISAT ASAR data. The pick-to-pick estimated displacement was 10 cm in west, 69 cm in south and 22 cm in vertical directions. We then used strain analysis to study coseismic surface deformation of the earthquake. Finite differences and finite element as two numerical solutions were applied in order to compute the strain tensors. Furthermore, dilation and shear parameters were derived using the strain tensors. Finite differences results showed the maximum expansion of 0.002 and maximum contraction of 0.003. The amounts of maximum shear in xy, xz and yz planes were estimated using finite differences method as 0.05, 0.1 and 0.049, respectively. The maximum expansion and contraction were computed as 0.006 and 0.005, respectively, using finite element approach. Moreover, the maximum shear in xy, xz and yz planes obtained by finite element method was 0.2, 0.4 and 0.19, respectively.