Evaluation of the fishery status for King Soldier Bream Argyrops spinifer in Pakistan using the software CEDA and ASPIC

Catch and effort data were analyzed to estimate the maximum sustainable yield(MSY) of King Soldier Bream, Argyrops spinifer(Forssk?l, 1775, Family: Sparidae), and to evaluate the present status of the fish stocks exploited in Pakistani waters. The catch and effort data for the 25-years period 1985–2009 were analyzed using two computer software packages, CEDA(catch and effort data analysis) and ASPIC(a surplus production model incorporating covariates). The maximum catch of 3 458 t was observed in 1988 and the minimum catch of 1 324 t in 2005, while the average annual catch of A. spinifer over the 25 years was 2 500 t. The surplus production models of Fox, Schaefer, and Pella Tomlinson under three error assumptions of normal, log-normal and gamma are in the CEDA package and the two surplus models of Fox and logistic are in the ASPIC package. In CEDA, the MSY was estimated by applying the initial proportion(IP) of 0.8, because the starting catch was approximately 80% of the maximum catch. Except for gamma, because gamma showed maximization failures, the estimated results of MSY using CEDA with the Fox surplus production model and two error assumptions, were 1 692.08 t(R 2 =0.572) and 1 694.09 t( R 2 =0.606), respectively, and from the Schaefer and the Pella Tomlinson models with two error assumptions were 2 390.95 t( R 2 =0.563), and 2 380.06 t( R 2 =0.605), respectively. The MSY estimated by the Fox model was conservatively compared to the Schaefer and Pella Tomlinson models. The MSY values from Schaefer and Pella Tomlinson models were the same. The computed values of MSY using the ASPIC computer software program with the two surplus production models of Fox and logistic were 1 498 t(R 2 =0.917), and 2 488 t( R 2 =0.897) respectively. The estimated values of MSY using CEDA were about 1 700–2 400 t and the values from ASPIC were 1 500–2 500 t. The estimates output by the CEDA and the ASPIC packages indicate that the stock is overfished, and needs some effective management to reduce the fishing effort of the species in Pakistani waters.     

Effect of Shale Distribution on Hydrocarbon Sands Integrated with Anisotropic Rock Physics for AVA Modelling: A Case Study

Shales can be distributed in sand through four different ways; laminated, structural, dispersed and any combination of these aforementioned styles. A careful analysis of well log data is required for the determination of shale distribution in sand affecting its reservoir quality. The objective of this study is to characterize the effect of shale distribution on reservoir quality of sands using well log data. The correlation of well data in terms of lithology has revealed four sand and three shale layers in Lower Goru Formation acting as a major reservoir in the study area. Our results indicate that the laminated type of shale distribution prevails at the Basal sand level, which does not affect its reservoir quality greatly. The remaining layers of variable vertical extent show a variety of shale distribution models affecting their reservoir quality adversely. We also present anisotropic rock physics modelling for AVA analysis at Basal sand level.     

Seismic characterization of reservoirs with multiple fracture sets using velocity and attenuation anisotropy data

Knowledge about the spatial distribution of the fracture density and the azimuthal fracture orientation can greatly help in optimizing production from fractured reservoirs. Frequency-dependent seismic velocity and attenuation anisotropy data contain information about the fractures present in the reservoir. In this study, we use the measurements of velocity and attenuation anisotropy data corresponding to different seismic frequencies and azimuths to infer information about the multiple fracture sets present in the reservoir. We consider a reservoir model with two sets of vertical fractures characterized by unknown azimuthal fracture orientations and fracture densities. Frequency-dependent seismic velocity and attenuation anisotropy data is computed using the effective viscoelastic stiffness tensor and solving the Christoffel equation. A Bayesian inversion method is then applied to measurements of velocity and attenuation anisotropy data corresponding to different seismic frequencies and azimuth to estimate the azimuthal fracture orientations and the fracture densities, as well as their uncertainties. Our numerical examples suggest that velocity anisotropy data alone cannot recover the unknown fracture parameters. However, an improved estimation of the unknown fracture parameters can be obtained by joint inversion of velocity and attenuation anisotropy data.     

An integrated multi-azimuth VSP study for fracture characterization in the vicinity of a well

We present the analysis of a multi-azimuth vertical seismic profiling data set that has been acquired in a tight gas field with the objective of characterizing fracture distributions using seismic anisotropy. We investigate different measurements of anisotropy, which are shear-wave splitting, P-wave traveltime anisotropy and azimuthal amplitude variation with offset. We find that for our field case shear-wave splitting is the most robust measure of azimuthal anisotropy, which is clearly observed over two distinct intervals in the target. We compare the results of the vertical seismic profiling analysis with other borehole data from the same well. Cross-dipole sonic and Formation MicroImager data from the reservoir section suggest that no open fractures intersect the well or are present within half a metre of the borehole wall. Furthermore, a detailed dispersion analysis of the sonic scanner data provides no indication of stress-induced seismic anisotropy along the logged borehole section. We therefore explain the azimuthal anisotropy measured in the vertical seismic profiling data with a model that contains discrete fracture corridors, which do not intersect the well itself but lie within the vertical seismic profiling investigation radius. We show that such a model can reproduce some basic characteristics of azimuthal anisotropy observed in the vertical seismic profiling data. The model is also consistent with well test data that suggest the presence of a fracture corridor away from the well. With this study we demonstrate the necessity of integrating different data types that investigate different scales of rock volume and can provide complementary information for understanding the characteristics of fracture networks in the subsurface.     

Characterization of fractured reservoirs using a consistent stiffness‐permeability model: focus on the effects of fracture aperture

In this paper we propose a method for the characterization of naturally fractured reservoirs by quantitative integration of seismic and production data. The method is based on a consistent theoretical frame work to model both effective hydraulic and elastic properties of fractured porous media and a (non‐linear) Bayesian method of inversion that provides information about uncertainties as well as mean (or maximum likelihood) values. We model a fractured reservoir as a porous medium containing a single set of vertical fractures characterized by an unknown fracture density, azimuthal orientation and aperture. We then look at the problem of fracture parameter estimation as a non‐linear inverse problem and try to estimate the unknown fracture parameters by joint inversion of seismic amplitude versus angle and azimuth data and dynamic production data. Once the fracture parameters have been estimated the corresponding effective stiffness and permeability tensors can be estimated using consistent models. A synthetic example is provided to clearly explain and test the workflow. It shows that seismic and production data complement each other, in the sense that the seismic data resolve a non‐uniqueness in the fracture orientation and the production data help to recover the true fracture aperture and permeability, because production data are more sensitive to the fracture aperture than the seismic data.     

Rainfall–runoff,flood inundation and sensitivity analysis of the 2014 Pakistan flood in the Jhelum and Chenab river basin

ABSTRACT

The major flood of 2014 in the two eastern, transboundary rivers, the Jhelum and Chenab in Punjab, Pakistan, was simulated using the two-dimensional rainfall–runoff model. The simulated hydrograph showed good agreement with the observed discharge at the model outlet and intervening barrages, with a Nash-Sutcliffe efficiency of 0.86 at the basin outlet. Further, simulated flood inundation extent showed good agreement with the MODIS imagery with a fit (%) of 0.87. For some affected areas that experienced short-duration flooding, local housing damage data confirmed the simulated results. Besides the rainfall–runoff and flood inundation modelling, parameter sensitivity analysis was undertaken to identify the influence of various river and floodplain parameters. The analysis showed that the river channel geometric parameters and the roughness coefficients exerted the primary influence over flood extent and peak flow.     

Anisotropic permeability in fractured reservoirs from frequency‐dependent seismic Amplitude Versus Angle and Azimuth data

Attempts have previously been made to predict anisotropic permeability in fractured reservoirs from seismic Amplitude Versus Angle and Azimuth data on the basis of a consistent permeability‐stiffness model and the anisotropic Gassmann relations of Brown and Korringa. However, these attempts were not very successful, mainly because the effective stiffness tensor of a fractured porous medium under saturated (drained) conditions is much less sensitive to the aperture of the fractures than the corresponding permeability tensor. We here show that one can obtain information about the fracture aperture as well as the fracture density and orientation (which determines the effective permeability) from frequency‐dependent seismic Amplitude Versus Angle and Azimuth data. Our workflow is based on a unified stiffness‐permeability model, which takes into account seismic attenuation by wave‐induced fluid flow. Synthetic seismic Amplitude Versus Angle and Azimuth data are generated by using a combination of a dynamic effective medium theory with Rüger's approximations for PP reflection coefficients in Horizontally Transversely Isotropic media. A Monte Carlo method is used to perform a Bayesian inversion of these synthetic seismic Amplitude Versus Angle and Azimuth data with respect to the parameters of the fractures. An effective permeability model is then used to construct the corresponding probability density functions for the different components of the effective permeability constants. The results suggest that an improved characterization of fractured reservoirs can indeed be obtained from frequency‐dependent seismic Amplitude Versus Angle and Azimuth data, provided that a dynamic effective medium model is used in the inversion process and a priori information about the fracture length is available.     

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.