Seismic modelling for reservoir studies: a comparison between convolutional and full-waveform methods for a deep-water turbidite sandstone reservoir

Two seismic modelling approaches, that is, two-dimensional pre-stack elastic finite-difference and one-dimensional convolution methods, are compared in a modelling exercise over the fluid-flow simulation model of a producing deep-water turbidite sandstone reservoir in the West of Shetland Basin. If the appropriate parameterization for one-dimensional convolution is used, the differences in three-dimensional and four-dimensional seismic responses from the two methods are negligible. The key parameters to ensure an accurate seismic response are a representative wavelet, the distribution of common-depth points and their associated angles of incidence. Conventional seismic images generated by the one-dimensional convolutional model suffer from lack of continuity because it only accounts for vertical resolution. After application of a lateral resolution function, the convolutional and finite-difference seismic images are very similar. Although transmission effects, internal multiples and P-to-S conversions are not included in our convolutional modelling, the subtle differences between images from the two methods indicates that such effects are of secondary nature in our study. A quantitative comparison of the (normalized root-mean-square) amplitude attributes and waveform kinematics indicates that the finite-difference approach does not offer any tangible benefit in our target-oriented seismic modelling case study, and the potential errors from one-dimensional convolution modelling are comparatively much smaller than the production-induced time-lapse changes.     

Assessing Submerged Vegetation Roughness in Streambed under Clear Water Condition Using Physical Modeling

Water Resources - Roughness coefficient, also called Manning’s coefficient, is one of the most important hydraulic parameters in the rivers. This coefficient, in addition to the flow...     

Predictive stability indicator: a novel approach to configuring a real‐time hybrid simulation

Real‐time hybrid simulation (RTHS) is an effective and versatile tool for the examination of complex structural systems with rate dependent behaviors. To meet the objectives of such a test, appropriate consideration must be given to the partitioning of the system into physical and computational portions (i.e., the configuration of the RTHS). Predictive stability and performance indicators (PSI and PPI) were initially established for use with only single degree‐of‐freedom systems. These indicators allow researchers to plan a RTHS, to quantitatively examine the impact of partitioning choices on stability and performance, and to assess the sensitivity of an RTHS configuration to de‐synchronization at the interface. In this study, PSI is extended to any linear multi‐degree‐of‐freedom (MDOF) system. The PSI is obtained analytically and it is independent of the transfer system and controller dynamics, providing a relatively easy and extremely useful method to examine many partitioning choices. A novel matrix method is adopted to convert a delay differential equation to a generalized eigenvalue problem using a set of vectorization mappings, and then to analytically solve the delay differential equations in a computationally efficient way. Through two illustrative examples, the PSI is demonstrated and validated. Validation of the MDOF PSI also includes comparisons to a MDOF dynamic model that includes realistic models of the hydraulic actuators and the control‐structure interaction effects. Results demonstrate that the proposed PSI can be used as an effective design tool for conducting successful RTHS. Copyright © 2016 John Wiley & Sons, Ltd     

Monitoring hawksbill turtle nesting sites in some protected areas from the Persian Gulf

Iranian nesting populations of the critically endangered hawksbill turtle(Eretmochelys imbricate) are some of the most important in the Indian Ocean. In this study, four of the most important hawksbill nesting grounds in the Persian Gulf, situated within three Iranian marine protected areas, were surveyed during nesting season,including Nakhiloo, Ommolgorm and Kharko Islands and the mainland beaches of the Naiband Marine-Coastal National Park(NMCNP). We present GIS maps of these key nesting grounds and describe sand texture of key nesting zones, along with conservation recommendations. About 9.2(28.3%) out of 32.5 km of all shores surveyed in this study were used by nesting hawksbill turtles follows: Nakhiloo: 1.4 km(52% of potential nesting area);Ommolgorm: 1.94 km(40%); Kharko: 3.4 km(28%), and NMCNP: 2.46 km(18.9%). The average nesting density was calculated as 131 nests/km at Nakhiloo, 76 nests/km at Ommolgorm, 7 nests/km at Kharko, and 15 nests per km at NMCNP. Highest nesting density was observed in Nakhiloo and Ommolgorm. It is thought that high hawksbill nesting density in these islands seems likely a result of limiting adequate nesting shores rather than the size of population, and also low density in Kharko and NMCNP more related to past and current pressures and low population density. With the exception of Ommolgorm Island, sands at the nesting grounds were well sorted.Grain size indicated that female hawksbill turtles in the Iranian Persian Gulf nest in sands that are generally mixed, with mean grain size ranging from coarse sands(0.4Φ;～0.5–1 mm) to fine sands(2Φ;～0.25 mm). We provide and discuss conservation recommendations and suggestions for future.     

Validation of basaltic glass adsorption capabilities from geothermal arsenic in a basaltic aquifer: A case study from Bjarnarflag power Station,Iceland

Arsenic is a carcinogen known for its acute toxicity to organisms.Geothermal waters are commonly high in arsenic,as shown at the Bjarnarflag Power Plant,Iceland(～224 μg/kg of solvent).Development of geothermal energy requires adequate disposal of arsenic-rich waters into groundwater/geothermal systems.The outcome of arsenic transport models that assess the effect of geothermal effluent on the environment and ecosystems may be influenced by the sensitivity of hydraulic parameters.However,previous such studies in Iceland do not consider the sensitivity of hydraulic parameters and thereby the interpretations remain unreliable.Here we used the Lake Myvatn basaltic aquifer system as a case study to identify the sensitive hydraulic parameters and assess their role in arsenic transport.We develop a one-dimensional reactive transport model(PHREEQC ver.2.),using geochemical data from Bjarnarflag,Iceland.In our model,arsenite(H_3 ASO_3)was predicted to be the dominant species of inorganic arsenic in both groundwater and geothermal water.Dilution reduced arsenic concentration below～5 μg/kg.Adsorption reduced the residual contamination below～0.4μg/kg at 250 m along transect.Based on our modelling,we found volumetric input to be the most sensitive parameter in the model.In addition,the adsorption strength of basaltic glass was such that the physical hydrogeological parameters,namely:groundwater velocity and longitudinal dispersivity had little influence on the concentration profile.     

Optimum placement and characteristics of velocity-dependent dampers under seismic excitation

In this study,through novel drift-based equations of motion in the frequency domain,optimum placement and characteristics of linear velocity-dependent dampers are investigated.In this study,the sum of the square of the absolute values of transfer matrix elements for interstory drifts is considered as the optimization index.Optimum placement and characteristics of dampers are simultaneously obtained by minimizing the optimization index through an incremental procedure.In each step of the procedure,a predefined value is considered as the damper characteristic.The optimum story for this increment is selected such that it leads to a minimum value for the optimization index.The procedure is repeated for the next increments until the optimization index meets its target value,which is obtained according to the desired damping ratio for the overall structure.In other words,the desired overall damping ratio is the input to the proposed procedure,and the optimal placement and characteristics of the dampers are its output.It is observed that the optimal placement of a velocitydependent damper depends on the damping coefficient of the added damper,frequency of the excitation,and distribution of the mass,stiffness,and inherent damping of the main structure.     

Optimum geometry of tuned liquid column-gas damper for control of offshore jacket platform vibrations under seismic excitation

In this study, the effectiveness of a tuned liquid column-gas damper, TLCGD, on the suppression of seismic-induced vibrations of steel jacket platforms is evaluated. TLCGD is an interesting choice in the case of jacket platforms because it is possible to use the structural elements as the horizontal column of the TLCGD. The objective here is to find the optimum geometric parameters, namely orientation and configuration of vertical columns, length ratio, and area ratio of the TLCGD, considering nonlinear damping of the TLCGD and water-structure interaction between the jacket platform and sea water. The effects of different characteristics of ground motion such as PGA and frequency content on the optimum geometry are also investigated and it is observed that these features have some influence on the optimum area ratio. Finally it is observed that pulse arrangement of ground acceleration is one of the most important parameters affecting the efficiency of a TLCGD. In other words, it is found that the TLCGD’s capability to reduce the RMS responses depends only on the frequency content of the ground acceleration, but its capability to reduce the maximum responses depends on both the frequency content and the pulse arrangement of the ground acceleration.     

NMR Parameters Determination through ACE Committee Machine with Genetic Implanted Fuzzy Logic and Genetic Implanted Neural Network

Free fluid porosity and rock permeability, undoubtedly the most critical parameters of hydrocarbon reservoir, could be obtained by processing of nuclear magnetic resonance (NMR) log. Despite conventional well logs (CWLs), NMR logging is very expensive and time-consuming. Therefore, idea of synthesizing NMR log from CWLs would be of a great appeal among reservoir engineers. For this purpose, three optimization strategies are followed. Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models. Results indicated that optimization of traditional ANN and FL model using GA-PS technique significantly enhances their performances. Furthermore, the ACE committee of aforementioned models produces more accurate and reliable results compared with a singular model performing alone.     

Application of Electrical Resistivity Imaging for Engineering Site Investigation. A Case Study on Prospective Hospital Site,Varamin, Iran

The article addresses the application of electrical resistivity imaging for engineering site investigation in Pishva Hospital, Varamin, Iran. Some aqueduct shafts exist in the study area backfilled by loose materials. The goals of this study are to detect probable aqueduct tunnels and their depth, investigate filling quality in the shafts as well as connection(s) between them. Therefore, three profiles were surveyed by dipoledipole electrode array. Also, to investigate the potentially anomalous areas more accurately, five additional resistivity profiles were measured by a Combined Resistivity Sounding-Profiling array (CRSP). According to the results of 2-D inversion modelling, a main aqueduct tunnel was detected beneath the central part of the site. Finally, the resistivity pattern of the detected aqueduct system passing the investigated area was provided using the obtained results.