Characterization of small faults and fractures in a carbonate reservoir using waveform inversion, reverse time migration, and seismic attributes

Takougang, Eric M. Takam; Bouzidi, Youcef; Ali, Mohammed Y.

doi:10.1016/j.jappgeo.2018.12.012

Cited by 25 publications

(8 citation statements)

References 39 publications

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“…The workflow for the extraction of faults and fractures is explained in details in (Takam Takougang et al, 2018, 2019. The workflow was applied with success using 2D walkaway seismic data (Takam Takougang et al, 2019) and expanded to 3D (Takam Takougang et al, 2018). Here we provide an overview of the method.…”

Section: Methods and Resultsmentioning

confidence: 99%

Fractures extraction and associated intensity maps from 3D VSP data

Takougang

Ali

Bouzidi

et al. 2019

ASEG Extended Abstracts

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Section: Methods and Resultsmentioning

confidence: 99%

Fractures extraction and associated intensity maps from 3D VSP data

Takougang

Ali

Bouzidi

et al. 2019

ASEG Extended Abstracts

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“…Characterizing the remarkable heterogeneity of these systems requires detailed reservoir studies and high-quality information. Seismic data and studies from analogues are widely used in large-scale field settings (Biber et al 2018;Takam Takougang et al 2019). Various types of data acquired while drilling are nowadays available at reservoir and borehole scales.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic assessment of equivalent fracture aperture constrained on quasi-real-time drilling mud loss data

Patani

Colombo²,

Russo³

et al. 2022

J Petrol Explor Prod Technol

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We provide a rigorous workflow to quantify the effects of key sources of uncertainty associated with equivalent fracture aperture estimates w constrained through mud loss information acquired while drilling a well in a reservoir. A stochastic inverse modeling framework is employed to estimate the probability distribution of w. This choice is consistent with the quantity and quality of available data. The approach allows assessing the probability that values of w inferred from mud loss events exceed a given threshold. We rely on a streamlined analytical solution to model mud losses while drilling. We explicitly consider uncertainties associated with model parameters and forcing terms, including drilling fluid rheological properties and flow rates, pore fluid pressure, and dynamic drilling fluid pressure. A synthetic scenario is considered to provide a transparent reference setting against which our stochastic inverse modeling workflow can be appraised. The approach is then applied to a real-case scenario. The latter is associated with data monitored on a rig site. A direct comparison of the impact of data collected through two common techniques (respectively, relying on flow meter sensors or pump strokes) on the ensuing probability of w is provided. A detailed analysis of the uncertainty related to the level of data corruption is also performed, considering various levels of measurement errors. Results associated with the field setting suggest that the proposed workflow yields probability distribution of w that are compatible with interpretations relying on traditional analyses of image logs. Results stemming from direct and indirect flow data display similar shapes. This suggests the viability of the probabilistic inversion methodology to assist quasi-real-time identification of equivalent fracture apertures on the basis of routinely acquired information during drilling.

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“…The greater the similarity between the two data, the greater the coherence value, that is, the value approaches one. The greater the difference between the two, the smaller the coherence value will be close to zero, and if the two data are increasingly opposite, the coherence value will be close to negative one [19]. The coherence criterion commonly used in velocity analysis is the semblance [20].…”

Section: Introductionmentioning

confidence: 99%

Semblance Residual Moveout Analysis to Find Erorrs and Updating the Interval Velocity Model Mode in the Horizon Based Tomography Method

2020

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The tomography method requires an excellent initial velocity model. On the horizon based tomography, it will correct the travel time error of seismic waves along the horizon which is analysed using input results from the analysis of residual depth moveout. In this study, a semblance residual moveout analysis will be conducted after the interval velocity model has applied to the SBI field seismic data (CDP Gathers and RMS velocity). Based on the imaging results generated by the PSDM running process, an aperture value of 550 for inline and 800 for crossline is selected. PSDM generated from the initial interval velocity model has an acoustic impedance value between 1000 kg/m2s to 14339.2 kg/m2s. The PSDM process, residual moveout analysis, and horizon-based tomography are carried out iteratively until the error in the interval velocity model approaches zero. In this study, five iterations were performed. The resulting residual moveout is increasingly oscillating around zero after the 5th iteration, which indicates that the error in the interval velocity model is getting smaller. There are two types of residual moveout, namely residuals moveout positively and residuals moveout negatively. Residual moveout positive indicates that the velocity used is too high, while the residual moveout negative indicates that the velocity used is too low. The identification of interval velocity model errors with analysis of residual moveout semblance is calculated from depth gathers. The semblance residual moveout analysis is used for the Pre Stack Depth Migration (PSDM) depth image analysis stage along with the marker (well data). .

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Characterization of small faults and fractures in a carbonate reservoir using waveform inversion, reverse time migration, and seismic attributes

Cited by 25 publications

References 39 publications

Fractures extraction and associated intensity maps from 3D VSP data

Fractures extraction and associated intensity maps from 3D VSP data

Probabilistic assessment of equivalent fracture aperture constrained on quasi-real-time drilling mud loss data

Semblance Residual Moveout Analysis to Find Erorrs and Updating the Interval Velocity Model Mode in the Horizon Based Tomography Method

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