Impedance inversion method constrained with crosswell seismic data

Data seismik 3D (CDP gather) pada daerah penelitian dilakukan proses inversi prestack yaitu inversi AVO simultan untuk mengetahui sebaran hidrokarbon. Data seismik 3D terbentang dengan jangkauan inline 1003-1302 dan xline 5002-5300. Metode inversi AVO simultan dilakukan dengan data masukan berupa angle stack yang diinversi secara bersama-sama (simultan) untuk menghasilkan impedansi-P, impedansi-S dan densitas. Dari hasil inversi impedansi-P dan inversi impedansi-S didapatkan nilai lambda-rho dan mu-rho sebagai hasil turunannya. Kisaran nilai hasil inversi impedansi-P, impedansi-S, densitas, lambda-rho dan mu-rho pada porous limestone formasi Baturaja yaitu nilai impedansi-P sekitar 11000-13500 m/s*g/cc, nilai impedansi-S sekitar 6500-7400 m/s*g/cc, nilai densitas sekitar 2,52-2,6 g/cc, nilai lambda-rho sekitar 36-70 Gpa*g/cc dan nilai mu-rho sekitar 41-59 Gpa*g/cc. Berdasarkan map slice hasil inversi impedansi-P, map slice hasil inversi impedansi-S, map slice hasil inversi densitas, map slice hasil inversi lambda-rho dan map slice hasil inversi mu-rho dapat diketahui area persebaran hidrokarbon pada formasi Baturaja. Persebaran hidrokarbon berada di sekitar sumur TT.3D seismic data (CDP gather) in the study area was carried out a prestack inversion process, namely simultaneous AVO inversion to determine the distribution of hydrocarbons. 3D seismic data stretches with inline range 1003-1302 and xline 5002-5300. Simultaneous AVO inversion method is done with input data in the form of angle stack which is inverted together (simultaneously) to produce P-impedance, S-impedance and density. From the results of P-impedance inversion and S-impedance inversion, the values of lambda-rho and mu-rho are derived as a result of their derivatives. The range of values of P-impedance inversion, S-impedance, density, lambda-rho and mu-rho in porous limestone formation i.e. the P-impedance value around 11000-13500 m/s*g/cc, the S-impedance value around 6500-7400 m/s*g/cc, the density value around 2.52-2.6 g/cc, the lambda-value rho around 36-70 Gpa*g/cc and your value around 41-59 Gpa*g/cc. Based on the P-impedance inversion map slice, S-impedance inversion map slice, density inversion map slice, lambda-rho inversion map slice and mu-rho inversion map slice can be known the area of hydrocarbon distribution in the Baturaja formation. Hydrocarbon spread is around the TT well.

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Double-scale supervised inversion with a data-driven forward model for low-frequency impedance recovery

Geophysics ◽

10.1190/geo2020-0421.1 ◽

2021 ◽

pp. 1-102

Author(s):

Sanyi Yuan ◽

Shangxu Wang ◽

Wenjing Sang ◽

Xinqi Jiao ◽

Yaneng Luo

Keyword(s):

Seismic Data ◽

Inverse Operator ◽

Low Frequency ◽

Data Driven ◽

Inversion Method ◽

Initial Model ◽

Data Set ◽

Model Driven ◽

Impedance Inversion ◽

Double Scale

Low-frequency information is important in reducing the nonuniqueness of absolute impedance inversion and for quantitative seismic interpretation. In traditional model-driven impedance inversion methods, low-frequency impedance background is from an initial model and is almost unchanged during the inversion process. Moreover, the inversion results are limited by the quality of the modeled seismic data and the extracted wavelet. To alleviate these issues, we investigate a double-scale supervised impedance inversion method based on the gated recurrent encoder-decoder network (GREDN). We first train the decoder network of GREDN called the forward operator, which can map impedance to seismic data. We then implement the well-trained decoder as a constraint to train the encoder network of GREDN called the inverse operator. Besides matching the output of the encoder with broadband pseudo-well impedance labels, data generated by inputting the encoder output into the known decoder match the observed narrowband seismic data. Both the broadband impedance information and the already-trained decoder largely limit the solution space of the encoder. Finally, after training, only the derived optimal encoder is applied to unseen seismic traces to yield broadband impedance volumes. The proposed approach is fully data-driven and does not involve the initial model, seismic wavelet and model-driven operator. Tests on the Marmousi model illustrate that the proposed double-scale supervised impedance inversion method can effectively recover low-frequency components of the impedance model, and demonstrate that low frequencies of the predicted impedance originate from well logs. Furthermore, we apply the strategy of combining the double-scale supervised impedance inversion method with a model-driven impedance inversion method to process field seismic data. Tests on a field data set show that the predicted impedance results not only reveal a classical tectonic sedimentation history, but also match the corresponding results measured at the locations of two wells.

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A Solution of Imaging and Wave Impedance Inversion of Seismic Data

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.373-375.569 ◽

2013 ◽

Vol 373-375 ◽

pp. 569-573

Author(s):

Rui Yang ◽

Guang Xun Chen ◽

Pan Ke Qin ◽

Neng You Wu ◽

Jia Shun Yu

Keyword(s):

Seismic Data ◽

Wave Impedance ◽

Inversion Method ◽

Reflection Coefficients ◽

Inversion Result ◽

Impedance Model ◽

Impedance Inversion ◽

High Vertical Resolution ◽

And Inversion

In order to improve the resolution and accuracy of the inversion, this paper proposed a new inversion method. By introducing constraint sparse spike inversion, the new method can fully take the advantages of high vertical resolution of logging data and the preferable transverse continuity of the seismic data to improve the resolution of the profiles and the quality of imaging and inversion in specific areas. Experimental results showed that this solution can deduce more precise and reasonable inversion result than other inversion solution. Constraint sparse spike inversion can generate reflection coefficients with broad frequency band and solve the marking problems preferably, thereby makes the impedance model obtained from the inversion even close to the actual situation underground.

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Deepwater reservoir prediction using broadband seismic-driven impedance inversion and seismic sedimentology in the South China Sea

Interpretation ◽

10.1190/int-2018-0029.1 ◽

2018 ◽

Vol 6 (4) ◽

pp. SO17-SO29 ◽

Cited By ~ 1

Author(s):

Yaneng Luo ◽

Handong Huang ◽

Yadi Yang ◽

Qixin Li ◽

Sheng Zhang ◽

...

Keyword(s):

South China Sea ◽

South China ◽

Seismic Data ◽

Seismic Velocity ◽

The South China Sea ◽

Hydrocarbon Exploration ◽

The South ◽

Low Frequencies ◽

China Sea ◽

Impedance Inversion

In recent years, many important discoveries have been made in the marine deepwater hydrocarbon exploration in the South China Sea, which indicates the huge exploration potential of this area. However, the seismic prediction of deepwater reservoirs is very challenging because of the complex sedimentation, the ghost problem, and the low exploration level with sparse wells in deepwater areas. Conventional impedance inversion methods interpolate the low frequencies from well-log data with the constraints of interpreted horizons to fill in the frequency gap between the seismic velocity and seismic data and thereby recover the absolute impedance values that may be inaccurate and cause biased inversion results if wells are sparse and geology is complex. The variable-depth streamer seismic data contain the missing low frequencies and provide a new opportunity to remove the need to estimate the low-frequency components from well-log data. Therefore, we first developed a broadband seismic-driven impedance inversion approach using the seismic velocity as initial low-frequency model based on the Bayesian framework. The synthetic data example demonstrates that our broadband impedance inversion approach is of high resolution and it can automatically balance between the inversion resolution and stability. Then, we perform seismic sedimentology stratal slices on the broadband seismic data to analyze the depositional evolution history of the deepwater reservoirs. Finally, we combine the broadband amplitude stratal slices with the impedance inversion results to comprehensively predict the distribution of deepwater reservoirs. Real data application results in the South China Sea verify the feasibility and effectiveness of our method, which can provide a guidance for the future deepwater hydrocarbon exploration in this area.

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An impedance inversion method based on wavelet energy balancing

2013 International Conference on Computational Problem-Solving (ICCP) ◽

10.1109/iccps.2013.6893526 ◽

2013 ◽

Author(s):

Shengchuan Wang ◽

Zhenming Peng

Keyword(s):

Inversion Method ◽

Energy Balancing ◽

Wavelet Energy ◽

Impedance Inversion

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Traveltime information-based wave-equation inversion

Geophysics ◽

10.1190/1.3243073 ◽

2009 ◽

Vol 74 (6) ◽

pp. WCC27-WCC36 ◽

Cited By ~ 30

Author(s):

Yu Zhang ◽

Daoliu Wang

Keyword(s):

Wave Equation ◽

Conventional Method ◽

Seismic Data ◽

Waveform Inversion ◽

Back Propagation ◽

Velocity Model ◽

Data Fitting ◽

Inversion Method ◽

New Wave ◽

Seismic Record

We propose a new wave-equation inversion method that mainly depends on the traveltime information of the recorded seismic data. Unlike the conventional method, we first apply a [Formula: see text] transform to the seismic data to form the delayed-shot seismic record, back propagate the transformed data, and then invert the velocity model by maximizing the wavefield energy around the shooting time at the source locations. Data fitting is not enforced during the inversion, so the optimized velocity model is obtained by best focusing the source energy after a back propagation. Therefore, inversion accuracy depends only on the traveltime information embedded in the seismic data. This method may overcome some practical issues of waveform inversion; in particular, it relaxes the dependency of the seismic data amplitudes and the source wavelet.

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Seismic resolution enhancement in shale-oil reservoirs

Geophysics ◽

10.1190/geo2017-0765.1 ◽

2018 ◽

Vol 83 (5) ◽

pp. B281-B287 ◽

Cited By ~ 3

Author(s):

Xiwu Liu ◽

Fengxia Gao ◽

Yuanyin Zhang ◽

Ying Rao ◽

Yanghua Wang

Keyword(s):

Seismic Data ◽

Resolution Enhancement ◽

Oil Reservoirs ◽

Inversion Method ◽

Shale Oil ◽

Data Set ◽

Extension Method ◽

Seismic Resolution ◽

Full Band ◽

Shale Oil Reservoirs

We developed a case study of seismic resolution enhancement for shale-oil reservoirs in the Q Depression, China, featured by rhythmic bedding. We proposed an innovative method for resolution enhancement, called the full-band extension method. We implemented this method in three consecutive steps: wavelet extraction, filter construction, and data filtering. First, we extracted a constant-phase wavelet from the entire seismic data set. Then, we constructed the full-band extension filter in the frequency domain using the least-squares inversion method. Finally, we applied the band extension filter to the entire seismic data set. We determined that this full-band extension method, with a stretched frequency band from 7–70 to 2–90 Hz, may significantly enhance 3D seismic resolution and distinguish reflection events of rhythmite groups in shale-oil reservoirs.

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