A semiautomatic method to tie well logs to seismic data

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. V47-V54 ◽  
Author(s):  
Roberto H. Herrera ◽  
Mirko van der Baan

We evaluated a semiautomatic method for well-to-seismic tying to improve correlation results and reproducibility of the procedure. In the manual procedure, the interpreter first creates a synthetic trace from edited well logs, determines the most appropriate bulk time shift and polarity, and then applies a minimum amount of stretching and squeezing to best match the observed data. The last step resembles a visual pattern recognition task, which often requires some experience. We replaced the last step with a constrained dynamic time-warping technique, to help guide the interpreter. The method automatically determined the appropriate amount of local stretching and squeezing to produce the highest correlation between the original data and the created synthetic trace. The constraint ensured that stretching and squeezing were kept within reasonable bounds, as determined by the interpreter. Results compared well with the manual method, leading to ties along the entire trace length in contrast to the shorter analysis window in the conventional method. Yet, we advise against unsupervised applications because the method is intended as a guide instead of a fully automated blind approach.

2020 ◽  
Vol 8 (4) ◽  
pp. T917-T925
Author(s):  
Bo Zhang ◽  
Yahua Yang ◽  
Yong Pan ◽  
Hao Wu ◽  
Danping Cao

The accuracy of seismic inversion is affected by the seismic wavelet and time-depth relationship generated by the process of the seismic well tie. The seismic well tie is implemented by comparing the synthetic seismogram computed from well logs and the poststack seismogram at or nearby the borehole location. However, precise waveform matching between the synthetic seismogram and the seismic trace does not guarantee an accurate tie between the elastic properties contained represented by the seismic data and well logs. We have performed the seismic well tie using the impedance log and the impedance inverted from poststack seismic data. We use an improved dynamic time warping to align the impedance log and impedance inverted from seismic data. Our workflow is similar to the current procedure of the seismic well tie except that the matching is implemented between the impedance log and the inverted impedance. The current seismic well-tie converges if there is no visible changes for the wavelets and time-depth relationship in the previous and current tying loops. Similarly, our seismic well tie converges if there are no visible changes for the wavelets, inverted impedance, and time-depth relationship in the previous and current tying loops. The real data example illustrates that more accurate inverted impedance is obtained by using the new wavelet and time-depth relationship.


2021 ◽  
pp. 1-65
Author(s):  
Huijing Fang ◽  
Yihuai Lou ◽  
Bo Zhang ◽  
Huaimin Xu ◽  
Man Lu

Stratigraphic correlation of well logs is based on interactive, interpreter-based pattern recognition. A skilled interpreter identifies similar patterns (such as upward fining and coarsening) in user-defined well sections and links them using either a conscious or subconscious stratigraphic model. This manual stratigraphic correlation of numerous wells in mature fields can be both time consuming and error prone. To expedite the process of stratigraphic correlation, we perform the semi-automatic stratigraphic correlation of wireline logs from multiple wells using the Improved Dynamic Time Warping (IDTW). The IDTW employs semblance, which compares the shape of the well logs, to replace the Euclidean distance in the pairwise error computation. The resulting error matrix is compatible with the lateral nonstationary variation of well logs in the same formation. The workflow begins with interpreting stratigraphic well tops on user-defined well sections that is similar to current process of stratigraphy analysis. The interpreted wells are then treated as reference wells to aid in interpreting well tops for other wells. Necessary manual interventions are incorporated during the process of the semi-automatic stratigraphic correlation. We applied the proposed method to two experimental fields: a sand-rich reservoir and a mud-rich reservoir. The applications illustrate that the proposed method performs well in aggradational strata and successfully predicts the discontinuities with manual interventions.


Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. V27-V37 ◽  
Author(s):  
Shuangquan Chen ◽  
Song Jin ◽  
Xiang-Yang Li ◽  
Wuyang Yang

Normal-moveout (NMO) correction is one of the most important routines in seismic processing. NMO is usually implemented by a sample-by-sample procedure; unfortunately, such implementation not only decreases the frequency content but also distorts the amplitude of seismic waveforms resulting from the well-known stretch. The degree of stretch increases with increasing offset. To minimize severe stretch associated with far offset, we use a dynamic time warping (DTW) algorithm to achieve an automatic dynamic matching NMO nonstretch correction, which does not handle crossing events and convoluted events such as thin layers. Our algorithm minimizes the stretch through an automatic static temporal correction of seismic wavelets. The local static time shifts are obtained using a DTW algorithm, which is a nonlinear optimization method. To mitigate the influence of noise, we evaluated a multitrace window strategy to improve the signal-to-noise ratio of seismic data by obtaining a more precise moveout correction at far-offset traces. To illustrate the effectiveness of our algorithm, we first applied our method to synthetic data and then to field seismic data. Both tests illustrate that our algorithm minimizes the stretch associated with far offsets, and the method preserves the amplitude fidelity.


Author(s):  
Chengyun Song ◽  
Lingxuan Li ◽  
Yaojun Wang ◽  
Kunhong Li ◽  
Jiying Tuo

2015 ◽  
Vol 3 (4) ◽  
pp. SAE1-SAE7 ◽  
Author(s):  
Parvaneh Karimi ◽  
Sergey Fomel ◽  
Lesli Wood ◽  
Dallas Dunlap

Detection and interpretation of fault systems and stratigraphic features and the relationship between them are crucial for seismic interpretation and reservoir characterization. To provide better interpretation insight and to be able to extract overlooked features out of seismic data volumes, we have developed a new attribute that detects faults and other discontinuities while handling local nonstationary variations across them. First, we used predictive painting to form a structural prediction of seismic events from neighboring traces (left and right neighboring traces in 2D and neighboring traces in all directions around a reference trace in 3D) according to the local structural slopes. Then, we computed prediction residuals by subtracting each prediction from the original data, and we found the smallest prediction-error interval for each point that best represented discontinuity information at that point. The extracted fault information changed with location (spatially and temporally), and it was nonstationary. Conventional coherence measures operate on a spatial window of neighboring traces and a temporal (vertical) analysis window of samples above and below the analysis point, and they can hardly cope with nonstationarity in fault information. In contrast, in our method, neither temporal nor spatial windows were involved in coherence computation, which allowed us to honor nonstationary changes of fault information and to achieve high resolution in the vertical and lateral directions. To assess the performance of the proposed attribute, we compared it with the conventional coherence attribute over the same data set. The comparison demonstrated the effectiveness of discontinuity detection using predictive coherence and showed its value in extracting additional information from seismic data.


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