China University of Petroleum

About: China University of Petroleum is a education organization based out in Beijing, China. It is known for research contribution in the topics: Catalysis & Oil shale. The organization has 39802 authors who have published 39151 publications receiving 483760 citations. The organization is also known as: Zhōngguó Shíyóu Dàxué & China University of Petroleum (Beijing).

Study of Nanoparticle–Surfactant-Stabilized Foam as a Fracturing Fluid

Abstract: The development of hydraulic fracturing has created a huge demand for fracturing fluids with high performance and low formation damage in recent years. In this paper, a foam stabilized by partially hydrophobic modified SiO2 nanoparticles and sodium dodecyl benzenesulfonate (SDBS) was studied as a fracturing fluid. The properties of SiO2/SDBS foam such as rheology, proppant suspension, filtration, and core damage were investigated. The experimental data showed that the stability and thermal adaptability of sodium dodecyl benzenesulfonate (SDBS) foam increased when silica (SiO2) nanoparticles were added. The surface tension of SDBS dispersion almost did not change after SiO2 nanoparticles were added; however, the dilational viscoelasticity of the interface increased, indicating that the SiO2 nanoparticles attached to the interface and formed a stronger viscoelasticity layer to resist the external disturbance. The proppant settling velocity in the SiO2/SDBS foam was found to be 2 orders of magnitude lower th...

AVO inversion and poroelasticity with P- and S-wave moduli

Abstract: The fluid term in the Biot-Gassmann equation plays an important role in reservoir fluid discrimination. The density term imbedded in the fluid term, however, is difficult to estimate because it is less sensitive to seismic amplitude variations. We combined poroelasticity theory, amplitude variation with offset (AVO) inversion, and identification of P- and S-wave moduli to present a stable and physically meaningful method to estimate the fluid term, with no need for density information from prestack seismic data. We used poroelasticity theory to express the fluid term as a function of P- and S-wave moduli. The use of Pand S-wave moduli made the derivation physically meaningful and natural. Then we derived an AVO approximation in terms of these moduli, which can then be directly inverted from seismic data. Furthermore, this practical and robust AVO-inversion technique was developed in a Bayesian framework. The objective was to obtain the maximum a posteriori solution for the P-wave modulus, S-wave modulus, and density. Gaussian and Cauchy distributions were used for the likelihood and a priori probability distributions, respectively. The introduction of a low-frequency constraint and statistical probability information to the objective function rendered the inversion more stable and less sensitive to the initial model. Tests on synthetic data showed that all the parameters can be estimated well when no noise is present and the estimated P- and S-wave moduli were still reasonable with moderate noise and rather smooth initial model parameters. A test on a real data set showed that the estimated fluid term was in good agreement with the results of drilling.