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Journal Articles
Journal:
SPE Formation Evaluation
Publisher: Society of Petroleum Engineers (SPE)
SPE Form Eval 3 (02): 357–363.
Paper Number: SPE-16389-PA
Published: 01 June 1988
... 1987 1 6 1988 1 6 1988 Copyright 1988, Society of Petroleum Engineers pressure lag pressure drop sand layer fluid dynamics prediction subsidence reservoir characterization upstream oil & gas nonlinearity permeability rate-type model compaction behavior pressure-lag...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the 2010 SEG Annual Meeting, October 17–22, 2010
Paper Number: SEG-2010-3499
... 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 achieves results comparable to gabordecon on a nonstationary (Q attenuation...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
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
Publisher: Society of Exploration Geophysicists
Paper presented at the 2012 SEG Annual Meeting, November 4–9, 2012
Paper Number: SEG-2012-0010
... 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. This approach has showed some success but much is left to be done. We present in this paper a data...
Proceedings Papers
Publisher: Offshore Technology Conference
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
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 about this image found in The effect of a lagging approach on recovery predictions for tertiary non-N...
Images
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 about this image found in The effect of a lagging approach on recovery predictions for tertiary non-N...
Proceedings Papers
Publisher: Offshore Mediterranean Conference
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
Publisher: Society of Exploration Geophysicists
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
Publisher: Society of Exploration Geophysicists
Paper presented at the 1991 SEG Annual Meeting, November 10–14, 1991
Paper Number: SEG-1991-1387
... 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 interval, and the desired...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
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
Publisher: Society of Exploration Geophysicists
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
Publisher: Society of Exploration Geophysicists
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
Publisher: Society of Exploration Geophysicists
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
Publisher: Society of Exploration Geophysicists
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...
Proceedings Papers
Paper presented at the The 33rd International Ocean and Polar Engineering Conference, June 19–23, 2023
Paper Number: ISOPE-I-23-537
... in depth, and the best relationship between backcast , wave lag and prediction length was deduced. With the help of incident waves, the N-BEATs model could predict the heave motion close to one minute into the future. The model also performed well with noise, and the prediction accuracy still exceeds 85...
Images
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 about this image found in Cumulative-oil-production predictions for a 3D tertiary shear-thinning poly...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the Middle East Oil, Gas and Geosciences Show, February 19–21, 2023
Paper Number: SPE-213343-MS
... prediction methods and new estimation simulations based on neural networks that can predict long-term behaviors. united states government asia government deep learning complex reservoir lag elasticnet prediction neural network machine learning lstm upstream oil & gas differencing tight...
Proceedings Papers
Publisher: American Rock Mechanics Association
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0353
...-time-series features are elaborately selected to serve as model inputs. Then, the natural language processing technique is employed to represent non time-series features and reduce the dimensionality. Next, to solve the lag of time-series model in long-series prediction, the differences in ROP...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
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...
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