Velocity and Structural Modeling of Mesozoic Chiltan Limestone and Goru Formation for Hydrocarbon Evaluation in the Bitrisim Area, Lower Indus Basin, Pakistan

The present study focuses on building a workflow for structural interpretation and velocity modeling and implementing to Jurassic-Cretaceous succession (Chiltan Limestone and Massive sand of the Lower Goru Formation). 2D-Migrated seismic sections of the area are used as data set and in order to confirm the presence of hydrocarbons in the study area, P and S-wave seismic velocities are estimated from single-component seismic data. Some specific issues in the use of seismic data for modeling and hydrocarbon evaluation need to deal with including distinguishing the reservoir and cap rocks, and the effects of faults, folds and presence of hydrocarbons on these rocks. This study has carried out the structural interpretation and modeling of the seismic data for the identification of traps. The results demonstrate existence of appropriate structural traps in the form of horst and grabens in the area. 2D and 3D velocity modeling of the horizons indicates the presence of high velocity zones in the eastern half of the study while relatively low velocity zones are encountered in the western half of the area. Two wells were drilled in the study area (i.e. Fateh-01 and Ichhri-01) and both are dry. Immature hydrocarbons migration is considered as a failure reason for Fateh-01 and Ichhri-01 well.     

A modi?ed failure criterion for transversely isotropic rocks

A modified failure criterion is proposed to determine the strength of transversely isotropic rocks. Me-chanical properties of some metamorphic and sedimentary rocks including gneiss, slate, marble, schist, shale, sandstone and limestone, which show transversely isotropic behavior, were taken into consider-ation. Afterward, introduced triaxial rock strength criterion was modified for transversely isotropic rocks. Through modification process an index was obtained that can be considered as a strength reduction parameter due to rock strength anisotropy. Comparison of the parameter with previous anisotropy in-dexes in literature showed reasonable results for the studied rock samples. The modified criterion was compared to modified Hoek-Brown and Ramamurthy criteria for different transversely isotropic rocks. It can be concluded that the modified failure criterion proposed in this study can be used for predicting the strength of transversely isotropic rocks.     

Land use land cover dynamics as a function of changing demography and hydrology

This paper describes the spatiotemporal changes pertaining to land use land cover (LULC) and the driving forces behind these changes in Doodhganga watershed of Jhelum Basin. An integrated approach utilizing remote sensing and geographic information system (GIS) was used to extract information pertaining to LULC change. Multi-date LULC maps were generated by analyzing remotely sensed images of three dates which include LandSat TM 1992, LandSat ETM+ 2001 and IRS LISS-III 2005. The LULC information was extracted by adopting on-screen image interpretation technique in a GIS environment at 1:25,000 scale. Based on the analysis, changes were observed in the spatial extent of different LULC types over a period of 13 years. Significant changes were observed in the spatial extent of forest, horticulture, built-up and agriculture. Forest cover in the watershed has decreased by 1.47 %, Agricultural by 0.93 % while as built-up area has increased by 0.92 %. The net decrease in forest cover and agriculture land indicate the anthropogenic interference into surrounding natural ecosystems. From the study it was found that the major driving forces for these changes were population growth and changes in the stream discharge. The changes in the stream discharge were found responsible for the conversion of agricultural land into horticulture, as horticulture has increased by 1.14 % in spatial extent. It has been found that increasing human population together with decreasing stream discharge account for LULC changes in the watershed. Therefore, the existing policy framework needs to focus upon mitigating the impacts of forces responsible for LULC change so as to ensure sustainable development of land resources.     

Applications of hybrid genetic algorithms in seismic tomography

Almost all earth sciences inverse problems are nonlinear and involve a large number of unknown parameters, making the application of analytical inversion methods quite restrictive. In practice, most analytical methods are local in nature and rely on a linearized form of the problem equations, adopting an iterative procedure which typically employs partial derivatives in order to optimize the starting (initial) model by minimizing a misfit (penalty) function. Unfortunately, especially for highly non-linear cases, the final model strongly depends on the initial model, hence it is prone to solution-entrapment in local minima of the misfit function, while the derivative calculation is often computationally inefficient and creates instabilities when numerical approximations are used. An alternative is to employ global techniques which do not rely on partial derivatives, are independent of the misfit form and are computationally robust. Such methods employ pseudo-randomly generated models (sampling an appropriately selected section of the model space) which are assessed in terms of their data-fit. A typical example is the class of methods known as genetic algorithms (GA), which achieves the aforementioned approximation through model representation and manipulations, and has attracted the attention of the earth sciences community during the last decade, with several applications already presented for several geophysical problems.In this paper, we examine the efficiency of the combination of the typical regularized least-squares and genetic methods for a typical seismic tomography problem. The proposed approach combines a local (LOM) and a global (GOM) optimization method, in an attempt to overcome the limitations of each individual approach, such as local minima and slow convergence, respectively. The potential of both optimization methods is tested and compared, both independently and jointly, using the several test models and synthetic refraction travel-time date sets that employ the same experimental geometry, wavelength and geometrical characteristics of the model anomalies. Moreover, real data from a crosswell tomographic project for the subsurface mapping of an ancient wall foundation are used for testing the efficiency of the proposed algorithm. The results show that the combined use of both methods can exploit the benefits of each approach, leading to improved final models and producing realistic velocity models, without significantly increasing the required computation time.     

Turbulent mixing condensation nucleus counter

The construction and operating principles of the Turbulent Mixing Condensation Nucleus Counter (TM CNC) are described. Estimations based on the semiempirical theory of turbulent jets and the classical theory of nucleation and growth show the possibility of detecting particles as small as 2.5 nm without the interference of homogeneous nucleation. This conclusion was confirmed experimentally during the International Workshop on Intercomparison of Condensation Nuclei and Aerosol Particle Counters (Vienna, Austria). Number concentration, measured by the Turbulent Mixing CNC and other participating instruments, is found to be essentially equal.     

Prediction of the Madden�CJulian oscillation with the POAMA dynamical prediction system

Predictions of the Madden?CJulian oscillation (MJO) are assessed using a 10-member ensemble of hindcasts from POAMA, the Australian Bureau of Meteorology coupled ocean?Catmosphere seasonal prediction system. The ensemble of hindcasts was initialised from observed atmosphere and ocean initial conditions on the first of each month during 1980?C2006. The MJO is diagnosed using the Wheeler-Hendon Real-time Multivariate MJO (RMM) index, which involves projection of daily data onto the leading pair of eigenmodes from an analysis of zonal winds at 200 and 850?hPa and outgoing longwave radiation (OLR) averaged about the equator. Forecasts of the two component (RMM1 and RMM2) index are quantitatively compared with observed behaviour derived from NCEP reanalyses and satellite OLR using the bivariate correlation skill, root-mean-square error (RMSE), and measures of the MJO amplitude and phase error. Comparison is also made with a simple vector autoregressive (VAR) prediction model of RMM as a benchmark. Using the full hindcast set, we find that the MJO can be predicted with the POAMA ensemble out to about 21?days as measured by the bivariate correlation exceeding 0.5 and the bivariate RMSE remaining below ~1.4 (which is the value for a climatological forecast). The VAR model, by comparison, drops to a correlation of 0.5 by about 12?days. The prediction limit from POAMA increases by less than 2?days for times when the MJO has large initial amplitude, and has little sensitivity to the initial phase of the MJO. The VAR model, on the other hand, shows a somewhat larger increase in skill for times of strong MJO variability and has greater sensitivity to initial phase, with lower skill for times when MJO convection is developing in the Indian Ocean. The sensitivity to season is, however, greater for POAMA, with maximum skill occurring in the December?CJanuary?CFebruary season and minimum skill in June?CJuly?CAugust. Examination of the MJO amplitudes shows that individual POAMA members have slightly above observed amplitude after a spin-up of about 10?days, whereas examination of the MJO phase error reveals that the model has a consistent tendency to propagate the MJO slightly slower than observed. Finally, an estimate of potential predictability of the MJO in POAMA hindcasts suggests that actual MJO prediction skill may be further improved through continued development of the dynamical prediction system.