Density inversion from seismic using a trans-dimensional approach: A field dataset example
- Reetam Biswas (University of Texas at Austin) | Dhananjay Kumar (BP) | Mrinal Sen (University of Texas at Austin) | Akkel Paul (BP) | Katrina Packer (BP)
- Document ID
- Society of Exploration Geophysicists
- SEG International Exposition and Annual Meeting, 15-20 September, San Antonio, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Exploration Geophysicists
- Nonlinear, Inversion, Reservoir characterization, AVO/AVA, Prestack
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- 4 since 2007
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Commercial and low gas saturation (also called paleo-residual gas, PRG) both appear as bright amplitude on P-wave seismic data. This is a common exploration risk in Columbus basin. Since density has strong inverse correlation with gas saturation, it should effectively differentiate a zone of full gas saturation from a zone of PRG. However, extracting density from amplitude-variations-with-offset (AVO) seismic inversion can be challenging, due to weak sensitivity of seismic reflection amplitude to density, and lack of good quality seismic AVO data. With the recent improvements in seismic acquisition and processing technology that produce reliable AVO gathers, density estimates have improved. In addition, the seismic inverse problem is highly non-linear, and multiple solutions exist. We solve the inversion problem using a newly-developed stochastic tool using a trans-dimensional approach, which is based on a Bayesian framework. The number of model parameters is treated as a variable and is estimated along with the elastic parameters: P-wave, S-wave velocity and density. We use Reversible Jump Hamiltonian Monte Carlo (RJHMC) to sample models from a variable dimensional model space and obtain a globally optimum model. We also estimate uncertainty in our derived model. Here we apply RJHMC to seismic data from Columbus basin to sample the model space at all CDP locations. This approach is tested over a proven gas reservoir from Trinidad where petrophysical evidence suggests that density plays a pivotal role in reflectivity and good quality seismic data are available. We also quantify the uncertainty in our density estimates.
Presentation Date: Monday, September 16, 2019
Session Start Time: 1:50 PM
Presentation Time: 1:50 PM
Presentation Type: Oral
|File Size||1007 KB||Number of Pages||5|
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