Characterization of sandstone reservoir field “Q” sub-basin Jambi using the extended elastic impedance seismic inversion method

This study has been done to map the distribution of gas saturated sandstone reservoir by using stochastic seismic inversion in the “X” field, Bonaparte basin. Bayesian stochastic inversion seismic method is an inversion method that utilizes the principle of geostatistics so that later it will get a better subsurface picture with high resolution. The stages in conducting this stochastic inversion technique are as follows, (i) sensitivity analysis, (ii) well to seismic tie, (iii) picking horizon, (iv) picking fault, (v) fault modeling, (vi) pillar gridding, ( vii) making time structure maps, (viii) scale up well logs, (ix) trend modeling, (x) variogram analysis, (xi) stochastic seismic inversion (SSI). In the process of well to seismic tie, statistical wavelets are used because they can produce good correlation values. Then, the stochastic seismic inversion results show that the reservoir in the study area is a reservoir with tight sandstone lithology which has a low porosity value and a value of High acoustic impedance ranging from 30,000 to 40,000 ft /s*g/cc.

Download Full-text

PRESTACK SEISMIC INVERSION WITH STRUCTURAL CONSTRAINTS

Interpretation ◽

10.1190/int-2020-0209.1 ◽

2021 ◽

pp. 1-41

Author(s):

Dong Li ◽

Suping Peng ◽

rui Zhang ◽

Yinling Guo ◽

Yongxu Lu ◽

...

Keyword(s):

Signal To Noise Ratio ◽

Seismic Inversion ◽

Inversion Method ◽

Structural Constraints ◽

Local Smoothing ◽

Data Noise ◽

Improved Accuracy ◽

Prestack Seismic Inversion ◽

Influence Of Noise

Pre-stack seismic inversion usually suffers from the lower signal-to-noise ratio, which could result in unstable inversion results. The conventional multi-trace lateral constrained inversion blurs the steeply dipping layers, whereas the simple structural constrained inversion is affected by noise. To solve this issue, an inversion method with multiple constraints is proposed, which include 1) A local smoothing operator is used to suppress the inversion anomalies caused by data noise, 2) a difference operator is used to protect the stratum boundary, 3) a structural dipping constraint is used to enhance the characterization of the possible dipping stratum. The multi-constraint inversion method suppresses the inversion anomalies caused by data noise without blurring the stratum boundary. The effects of different constraints in the inversion process and the influence of noise on the inversion results are analyzed. In multi-constraint inversion, the regularization coefficient of each constraint operator is dynamically changed, thereby controlling the significance of each regularization term in the inversion. The proposed algorithm is tested on synthetic and field data, which demonstrates its effectiveness and improved accuracy on the inversion results.

Download Full-text

Mapping the Distribution and Characterization of Sandstone Reservoir Using Simultaneous Inversion Method in “OA” Field at Northern Bonaparte Basin

Journal of Physics Conference Series ◽

10.1088/1742-6596/1351/1/012045 ◽

2019 ◽

Vol 1351 ◽

pp. 012045

Author(s):

Oki Fimansyah Wiyatno ◽

M. Syamsu Rosid ◽

Humbang Purba

Keyword(s):

Inversion Method ◽

Simultaneous Inversion ◽

Sandstone Reservoir

Download Full-text

Characterization of gas hydrate systems on the Hikurangi margin (New Zealand) through geostatistical seismic and petrophysical inversion

Geophysics ◽

10.1190/geo2021-0018.1 ◽

2021 ◽

pp. 1-60

Author(s):

Francesco Turco ◽

Leonardo Azevedo ◽

Dario Grana ◽

Gareth J. Crutchley ◽

Andrew R. Gorman

Keyword(s):

New Zealand ◽

Gas Hydrate ◽

Seismic Data ◽

Effective Means ◽

Rock Physics ◽

Seismic Inversion ◽

Inversion Method ◽

Seismic Reflection Data ◽

Reflection Data

Quantitative characterization of gas hydrate systems on continental margins from seismic data is challenging, especially in regions where no well logs are available. However, probabilistical seismic inversion provides an effective means for constraining the physical properties of subsurface strata in such settings and analyzing the variability related to the results. We apply a workflow for the characterization of two deep-water gas hydrate reservoirs east of New Zealand, where high concentrations of gas hydrate have been inferred previously. We estimate porosity and gas hydrate saturation in the reservoirs from multi-channel seismic data through a two-step procedure based on geostatistical seismic and Bayesian petrophysical inversion built on a rock physics model for gas hydrate-bearing marine sediments. We found that the two reservoirs together host between 2.45 × 105 m3 and 1.72 × 106 m3 of gas hydrate, with the best estimate at 9.68 × 105 m3. This estimate provides a first-order assessment for further gas hydrate evaluations in the region. The two-step statistically based seismic inversion method is an effective approach for characterizing gas hydrate systems from long-offset seismic reflection data.

Download Full-text