[1] Geostatistical inverse modeling has been shown to be a viable alternative to synthesis Bayesian methods for estimating global continental-scale CO2 fluxes. This study extends the geostatistical approach to take advantage of spatially and temporally varying auxiliary data sets related to CO2 flux processes, which allow the inversion to capture more grid-scale flux variability and better cons...

We introduce a new open-source toolkit for the well-tie or wavelet extraction problem of estimating seismic wavelets from seismic data, time-to-depth information, and well-log suites. The wavelet extraction model is formulated as a Bayesian inverse problem, and the software will simultaneously estimate wavelet coefficients, other parameters associated with uncertainty in the time-to-depth mappi...

This paper follows a geostatistical approach for the evaluation, modelling and visualization of the possible local interactions between natural components and built-up elements in seismic risk analysis. This method, applied to old town centre of Potenza hilltop town, offers a new point of view for civil protection planning using kernel density and autocorrelation indexes maps to analyse macrose...

Porosity is one of the key parameters associated with oil reservoirs. Determination of this petrophysical parameter is an essential step in reservoir characterization. Among different linear and nonlinear prediction tools such as multi-regression and polynomial curve fitting, artificial neural network has gained the attention of researchers over the past years. In the present study, two-dimensi...

Changes in reservoir properties resulting from extracting hydrocarbons and injecting fluid are critical to optimize production. These properties can be characterized using waveform inversions of time-lapse seismic data. The conventional approach for analysis using waveform tomography is to take the difference of seismic inversion obtained using baseline and subsequent time-lapse datasets that a...

based on the convolutional model, a seismic trace is the convolution of seismic source wavelet and reflection coefficient series of the earth. seismic source wavelet estimation is one of the most important stages in processing and interpretation of seismic data. accurate estimation of wavelet increases the efficiency of the deconvolution and temporal resolution of seismic data. on the other han...

Time-lapse seismic data are widely used for monitoring timevariant subsurface changes. Conventional analysis provides qualitative information by comparing results from consecutive surveys, whereas waveform inversion can retrieve quantitative estimates of reservoir properties through seismic waveform fitting. The quantitative evaluation of the physical parameters obtained by waveform inversion a...

Geostatistical modeling of reservoir properties is common in the assessment of expected reservoir flow. Typically, static properties such as porosity, saturation and permeability are modeled with geostatistical techniques to quantify the level of uncertainty in reservoir characterization. Lately, practitioners have become concerned that purely statistical techniques do not sufficiently integrat...

Time-lapse (4D) seismic data sets have proven to be extremely useful for reservoir monitoring. Seismic-derived impedance estimates are commonly used as a 4D attribute to constrain updates to reservoir fluid flow models. However, 4D seismic estimates of P-wave impedance can contain significant errors associated with the effects of seismic noise and the inherent instability of inverse methods. Th...