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We have performed a set of inversions on a thinly bedded clastic reservoir from the West of Shetland. The inversion techniques comprise a data-driven deterministic inversion (contractor), a data-driven stochastic inversion (contractor), a model-driven deterministic inversion (proprietary), and a model-driven stochastic inversion (proprietary). The variability between the results obtained from these different inversion techniques is far greater than the variability between the realizations obtained from a single stochastic inversion. This shows that the main uncertainty associated with the seismic inversion is the parameterization of the inversion itself.
ABSTRACT Prestack basis pursuit AVA inversion that is developed to obtain sparse elastic reflectivities provides a means to improve accuracy and resolution of subsurface layer properties for interpretation. To overcome the ill-posed problem, constraints have been introduced to stabilize the inversion process and avoid meaningless solutions. Inappropriate use of constraints into basis pursuit inversion will compromise the inversion result. In this paper, we propose a new approach to incorporate background trends into the objective function to reduce the nonuniqueness of the solutions and enhance the stability and accuracy of the prestack basis pursuit inversion. A smoothing priori model constraint and a priori P-wave and S-wave velocity ratio constraint that are suitable for basis pursuit algorithm are built into the inversion process. Tests on both synthetic and real seismic data are shown to demonstrate the validity of the new approach. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 8:30 AM Presentation Time: 9:45 AM Location: 217D Presentation Type: Oral
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In this paper, we present an amplitude variation with azimuth (AVAZ) non-linear orthorhombic inversion workflow. The workflow integrates an inversion based on linearized orthorhombic PP-reflectivity equations and an inversion based on non-linear general Zoeppritz equations. The former is suitable for weak contrasts and the latter valid also for strong interfaces. The strong-contrast orthorhombic AVAZ inversion uses a quasi-Newton solver. Quasi-Newton methods find local minima and, as such, are dependent on the starting model supplied. To provide a good initial model for the non-linear inversion, we propose a workflow that uses the linearized solution. We describe the workflow and demonstrate it on a synthetic example.
Presentation Date: Monday, October 17, 2016
Start Time: 1:25:00 PM
Presentation Type: ORAL
Improving the resolution of seismic inversion is vital for the seismic inversion problems. Seismic stochastic inversion can make use of the high frequency information of logging data and improve the vertical resolution. The Markov chain Monte Carlo (MCMC) method is widely used in stochastic inversion at present. However conventional Markov chain Monte Carlo (MCMC) method has some limits. This paper introduces a new stochastic inversion method based on Quantum Metropolis-Hastings method to deal with the pre-stack seismic inversion problems.
Presentation Date: Thursday, October 20, 2016
Start Time: 11:00:00 AM
Presentation Type: ORAL