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Prediction lag

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Journal Articles
SPE Form Eval 3 (02): 357–363.
Paper Number: SPE-16389-PA
Published: 01 June 1988
... in the sandstone reservoir rock itself. This is supported by the fact that a rate-type compaction model recently introduced does indeed give a good description of the observed field behavior. pressure lag pressure drop sand layer fluid dynamics prediction subsidence reservoir characterization upstream...
Proceedings Papers

Paper presented at the 2010 SEG Annual Meeting, October 17–22, 2010
Paper Number: SEG-2010-3499
... it operates directly on the individual Gabor slices. We also prescribe the construction of nonstationary autocorrelation functions as an analysis tool. We then compare slicedecon with the more established Gabor deconvolution or gabordecon. When the prediction filtering is unit-lag, we show that slicedecon...
Proceedings Papers

Paper presented at the 2003 SEG Annual Meeting, October 26–31, 2003
Paper Number: SEG-2003-2032
... predictive deconvolution wavelet kernel reservoir characterization deconvolution artificial intelligence Predictive deconvolution after air-gun signature compensation John F. Parrish*, Periseis Company Summary Conventional predictive deconvolution can be very effective if the prediction lag is longer...
Proceedings Papers

Paper presented at the 2012 SEG Annual Meeting, November 4–9, 2012
Paper Number: SEG-2012-0010
... with partial success. The success of multiple elimination relies heavily on the ability to make an accurate water bottom model. The current trend in the industry for SWD is to derive a 2D predictive operator with a predictive lag calculated from bathymetry, thus making it a totally data driven method...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2000
Paper Number: OTC-12010-MS
... that the prediction lag of F pr is given by the shallowest multiplecontributing reflector. Figure 2: Prediction of surface multiples in a data driven approach: the data is used as multiple prediction operator in a spatial convolution along the surface coordinates. (Available in full paper) berkhout...
Images
The effect of a <span class="search-highlight">lagging</span> approach on recovery <span class="search-highlight">predictions</span> for tertiary non-N...
Published: 27 July 2010
Figure 14 The effect of a lagging approach on recovery predictions for tertiary non-Newtonian polymer flooding. The results obtained with the finite-difference simulator (black) and our streamline code (colored): iterative and lagging with long timesteps (100 days) in red and green, respectively, ... More
Images
The effect of a <span class="search-highlight">lagging</span> approach on recovery <span class="search-highlight">predictions</span> for tertiary non-N...
Published: 04 October 2009
Figure 14 The effect of a lagging approach on recovery predictions for tertiary non-Newtonian polymer flooding. In red are the results obtained with the finite difference simulator (line) and our streamline code (dots). Running our code in a lagging mode (black dots) gave recovery predictions clos... More
Proceedings Papers

Paper presented at the Offshore Mediterranean Conference and Exhibition, March 20–22, 2013
Paper Number: OMC-2013-046
... ikniaku 0 1 (a0=1) (5) and P i kvikyiaky 1 (6) with P i ikniakv 0 2 (a0=1) (7) The AR prediction of x(t) with a lag is where â(i) i=1,P represent the estimated AR coefficients and the variance of u(k) is minimal. Because x(t) and y(t) are generated by the same specific method always...
Proceedings Papers

Paper presented at the 2005 SEG Annual Meeting, November 6–11, 2005
Paper Number: SEG-2005-2092
... to be attenuated Set the predictive lag to be the minimum lag in this range Set the active part of the operator to equal the range of lags identified The implicit assumption here is that the strength of the multiple component at these lags in the autocorrelation relative to the zero lag value, is indicative...
Proceedings Papers

Paper presented at the 1991 SEG Annual Meeting, November 10–14, 1991
Paper Number: SEG-1991-1387
... most commonly used to increase the resolution of seismic data. Adaptability in the presence of noise is a prime reason for the popularity of this process. The deconvolution process is made effective by the right choice of prediction lag and filter length, which largely depend on data quality, sampling...
Proceedings Papers

Paper presented at the 2012 SEG Annual Meeting, November 4–9, 2012
Paper Number: SEG-2012-0154
... the predicted lag moveouts to the observed lag picks using 2- norm. The resulting probability density function (pdf) of the event location has the form: pdd(s | s1, . . . ,sNs ,V ) = 1 (2pi) NrNs 2 Ns i=1 Nr j=1 i, j ×exp 1 2 Ns i=1 Nr j=1 ( i, j ( si,s,r j |V ) i, j )2 , where we emphasize...
Proceedings Papers

Paper presented at the 2013 SEG Annual Meeting, September 22–27, 2013
Paper Number: SEG-2013-1221
... is an estimate of delayed time of short period reverberations. This lag, referred as predictive lag is then used in predictive de- convolution. The original trace is then added to multiple traces, each of which is time shifted of the order of 20 DOI httpdx.doi.org/10.1190/segam2013-1221.1© 2013 SEG SEG Houston...
Proceedings Papers

Paper presented at the 2016 SEG International Exposition and Annual Meeting, October 16–21, 2016
Paper Number: SEG-2016-13530712
... denotes estimated primaries, u denotes the original data, x denotes the 2D predictive filter and U denotes the convolution matrix. Additionally, q denotes the temporal predictive lag in time samples. 2 1k K and 0T denote the temporal length of the 2D predictive filter and the temporal length...
Proceedings Papers

Paper presented at the 1990 SEG Annual Meeting, September 23–27, 1990
Paper Number: SEG-1990-1670
... and from Tl to T2-p-K at l=K. The spatial crosscorrelation function has hJ+l lags so that the correct limits on x are from X1+2J to X2-2J. In practice it is generally desirable to degrade the solution slightly by changing these limits to allow for bad or missing data. It is important to predict the low...
Proceedings Papers

Paper presented at the SPE Middle East Oil & Gas Show and Conference, November 28–December 1, 2021
Paper Number: SPE-204626-MS
... arrivals of bins R1, R2, R3, R4, computed from the mud logging service company's predicted lag times (i.e., using both Equation 2 and Equation 4 ), to the NanoTag signals detected by Py-GCMS analysis, indicating positive detection with a green check-mark and a null detection result with a red X...
Proceedings Papers

Paper presented at the 2002 SEG Annual Meeting, October 6–11, 2002
Paper Number: SEG-2002-2194
... Summary Conventional predictive deconvolution is very good for suppressing normal incidence water bottom reverberations. However, the output signature can vary significantly with the value selected for the prediction distance (lag). Generalizing predictive deconvolution with relative entropy...
Images
Cumulative-oil-production <span class="search-highlight">predictions</span> for a 3D tertiary shear-thinning poly...
Published: 27 July 2010
Figure 18 Cumulative-oil-production predictions for a 3D tertiary shear-thinning polymer flood. (a) Predictions using streamlines (red) against that predicted also using our code but with assumptions contained in current simulators. In green are results with the same rheological representation wit... More
Proceedings Papers

Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0014
... ( chloro ) Nanotags was injected. Accurate Time Bit Depth TD Ref Lagged In Figure 5 we compare the nominal arrival of bins R1, R2, R3, R4, computed from the mud logging software (-2 min) Svc Co Time GMT - 0 (ft) (ft) Bit Depth predicted lag times, to the NanoTag signals detected by Py-GCMS analysis. More...
Proceedings Papers

Paper presented at the SPE Canada Heavy Oil Technical Conference, June 7–9, 2016
Paper Number: SPE-180710-MS
... in reaching better statistics. However, as it was pointed above the formula is very stable and robust. It takes only one or two additional readings (10-20 minutes) to achieve very good matches between the actual and predicted values. Summary A Lagged PVT Ratio Formula predicting the SAGD intake...
Proceedings Papers

Paper presented at the 2014 SEG Annual Meeting, October 26–31, 2014
Paper Number: SEG-2014-1301
... be carried out during the drilling process without incurring extra rig time. correlation convolution concept inversion higher-order correlation source location contour reservoir characterization seg denver 2014 convolution equation 8 prediction seismic event upstream oil &amp; gas time lag...

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