A seismic waveform inversion algorithm is proposed for the estimation of elastic soil properties using low amplitude, downhole array recordings. Based on a global optimization scheme in the wavelet domain, complemented by a local least-square's fit operator in the frequency domain, the hybrid scheme can efficiently identify the optimal solution vicinity in the stochastic search space, whereas the best-fit model detection is substantially accelerated through the local deterministic inversion. Results presented for selected aftershocks of the M w 7.0 Sanriku-Minami earthquake in Japan, recorded by the Kik-Net Strong Motion Network, illustrate robustness of the impedance structure estimation. By contrast, the attenuation structure is shown to be sensitive to the frequency content of seismic input data, attributed to the deterministic description of the continuum in the forward model that cannot simulate late arrivals of multiple-scattered energy. Sensitivity analyses illustrate that for the same forward model, results can be substantially different based on the definition of the objective function. It is concluded that even for engineering purposes, inversion should aim to decouple intrinsic and scattering attenuation mechanisms.
During the volcanic gas reservoirs development, stress-sensitivity will result in permeability decline with formation pressure drop, lowering gas production and affecting the whole gas reservoirs development program. On the basis of the stress-sensitivity experiments on volcanic rocks, the characteristic of stress-sensitivity in volcanic reservoirs is analyzed. On this basis, this paper studies the prediction method of gas well productivity in volcanic gas reservoirs with stress-sensitivity, and establishes the mathematical model of constant pressure production in volcanic gas reservoirs. The results show that the permeability of volcanic rocks has an exponential relationship with effective stress. The stronger the stress-sensitivity is, the more the gas well productivity losses under the same conditions. And the reservoir stress-sensitivity will increase the degree of gas well unsteady production decline.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.