Experimental study on attenuation of Stoneley wave under different fracture factors

To quantitatively determine the effect of different factors such as fracture width,dip angle,extension and filling material on Stoneley wave amplitude decreasing,the shock tube experiment method was changed from fixing the sample and vertically moving the sensor in the borehole to fixing the sensors along the shock tube wall and vertically moving the sample without drilling the borehole in it.The measurement accuracy and the signal-to-noise ratio of the first Stoneley wave were improved by the time corrections and amplitude corrections of Stoneley wave signals.At the same time,21 sets of core models with different fracture parameters were processed for this measurement method by using full-diameter carbonate core,and relative amplitudes were defined to characterize Stoneley wave amplitude decreasing.The experimental results show that the relative amplitude of Stoneley wave exponentially decreases with increasing fracture width.The relative amplitude of Stoneley wave linearly decreases with increasing fracture dip angle.The relative amplitude of Stoneley wave exponentially decreases with increasing fracture extension.The relative amplitude of Stoneley wave decreases with increasing the permeability of filling material in the fracture.Under the above four conditions,the fracture width has the greatest effect on the decreasing of Stoneley wave amplitude,followed by the fracture extension and the permeability of filling material,and finally the fracture dip angle.

A Stoneley wave method to detect interlaminar damage of metal layer composite pipe

The interlaminar defect is a major form of damage in metal layer composite pipes which are widely used in petroleum and chemical industry. In this paper, a Stoneley wave method is presented to detect interlaminar damage in laminated pipe structure. Stoneley wave possesses some good characteristics, such as high energy and large displacement at the interface and non-dispersive in the high-frequency, so the sensitivity of detecting interlaminar damage can be improved and the higher frequency can be used in damage detection compared with Lamb waves. Additionally, as the frequency increases, the wavelength of the Stoneley wave reduces. Thus, its ability to detect small defects at the interface is enhanced. Finite element model of metal layer composite pipe with interlaminar damage is used to simulate wave propagation of Lamb waves and Stoneley wave, respectively. The damage location is calculated by using the Stoneley wave signal obtained from finite element model, and then the results are compared with the actual damage locations. The simulation examples demonstrate that the Stoneley wave method can better identify the interlaminar damage in laminated pipe structure compared with Lamb waves.

Experimental verification of the detect interlaminar damage of a interface wave method to metal multilayer structure

The interface wave traveling along the bound- ary of two materials has been studied for nearly a century. However, experiments, engineering applications, and interface wave applications to the non-destructive inspec- tion of interlaminar composite have developed slowly. In this research, an experiment that applies Stoneley waves （a type of interfacial wave between two solid half-spaces） is implemented to detect the damage in a multilayer structure. The feasibility of this method is also verified. First, the wave velocity and wave structure of Stoneley waves at a perfectly bonded aluminum-steel interface are obtained by solving the Stoneley wave dispersion equation of two elastic half-spaces. Thereafter, an experiment is conducted to measure the Stoneley wave velocity of an aluminum- steel laminated beam and to locate interlaminar cracks by referring to the Stoneley wave velocity and echo wave time. Results indicate that the location error is less than 2%. Therefore, Stoneley waves show great potential as a non-destructive inspection method of a multilayer structure.

Assessing Leak Paths in the Cement Sheath of a Cased Borehole by Analysis of Monopole Wavefield Modes

Evaluation of possible leakage pathways of CO_(2) injected into geological formations for storage is essential for successful Carbon Capture and Storage(CCS).A channel in the borehole cement,which secures the borehole casing to the formation,may allow CO_(2) to escape.Risk assessment and remediation decisions about the pres-ence of such channels depend on channel parameters:radial position r from the center of the borehole;channel thickness d;azimuthal positionφof the channel;and az-imuthal extentθof the channel.Current state-of-the-art cement-bond logging technology,which uses only the first arrival at a centralized borehole receiver,can diagnose limited details about CO_(2) leak channels.To accurately characterize the possible leak paths in the cement,we use a 3-dimensional finite-difference method to investigate the use of the abundant data collected by a modernized monopole sonic tool that contains an array of azimuthally distributed receivers.We also investigate how to improve the tool design to acquire even more useful information.For cases where borehole fluid is either water or supercritical CO_(2),we investigate various receiver geometries,multi-modal analyses of multi-frequency data to discover the type of logging tool that provides the best information for CCS management.We find that an appropriate choice of wave modes,source frequencies,source polarities,and receiver locations and off-sets provides sensitivity to d,φ,θ.The amplitude of the first arrival from a monopole source is sensitive toθ.Amplitudes at receivers at different azimuths are sensitive toφ.The slow Stoneley mode(ST2)velocity is sensitive to d,but ST2 is not easy to pick whenθand d are small.Further improvement is necessary to provide comprehensive information about possible flow channels in casing cement.

A comparative study of 3D FZI and electrofacies modeling using seismic attribute analysis and neural network technique:A case study of Cheshmeh-Khosh Oil field in Iran

Electrofacies are used to determine reservoir rock properties,especially permeability,to simulate fluid flow in porous media.These are determined based on classification of similar logs among different groups of logging data.Data classification is accomplished by different statistical analysis such as principal component analysis,cluster analysis and differential analysis.The aim of this study is to predict 3D FZI(flow zone index)and Electrofacies(EFACT)volumes from a large volume of 3D seismic data.This study is divided into two parts.In the first part of the study,in order to make the EFACT model,nuclear magnetic resonance(NMR)log parameters were employed for developing an Electrofacies diagram based on pore size distribution and porosity variations.Then,a graph-based clustering method,known as multi resolution graph-based clustering(MRGC),was employed to classify and obtain the optimum number of Electrofacies.Seismic attribute analysis was then applied to model each relaxation group in order to build the initial 3D model which was used to reach the final model by applying Probabilistic Neural Network(PNN).In the second part of the study,the FZI 3D model was created by multi attributes technique.Then,this model was improved by three different artificial intelligence systems including PNN,multilayer feed-forward network(MLFN)and radial basis function network(RBFN).Finally,models of FZI and EFACT were compared.Results obtained from this study revealed that the two models are in good agreement and PNN method is successful in modeling FZI and EFACT from 3D seismic data for which no Stoneley data or NMR log data are available.Moreover,they may be used to detect hydrocarbon-bearing zones and locate the exact place for producing wells for the future development plans.In addition,the result provides a geologically realistic spatial FZI and reservoir facies distribution which helps to understand the subsurface reservoirs heterogeneities in the study area.