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Abstract Accurate mapping of internal depositional architectural elements of a Pliocene-aged gas-bearing turbidite reservoir of the Mediterranean Basin into discrete 3D geobodies has been achieved through applying innovative workflow assisted by the convolutional neural network. The mapped reservoir depositional architectures have been integrated to the acoustic and elastic properties inverted form 3D seismic data to build robust multi-realizations reservoir static models. These models have been used to optimize the appraisal and development well locations and accurately assess the gas initial in-place of the discovery. Four wells have been sited utilizing the results of the constructed models. The wells have been successfully drilled and added 175 Million standard cubic feet in a day (MMscf/d) which obviously improve the commercial value of the project. The workflow is a major step in accurate delineation of the internal depositional architectural elements of the deep-water turbidite reservoirs of the Mediterranean Basins, as well as in other locations/basins where similar settings exist. By applying the workflow, the subsurface complexities were revealed with the artificial intelligence algorithms, uncertainties were captured, risks were reduced and project commercial value was uplifted.
- North America > United States (0.93)
- Africa > Middle East > Egypt (0.29)
- North America > Trinidad and Tobago > Trinidad > North Atlantic Ocean > Columbus Basin > South East Galeota Block > Cannonball Field (0.99)
- Asia > Middle East > Turkey > Mediterranean Sea > Mediterranean Basin > Cilicia Basin (0.99)
- Europe > Middle East > Malta > Mediterranean Sea (0.89)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- (2 more...)
Water contact mapping and saturation estimation using simultaneous inversion of time-lapse seismic data constrained by fluid substitution and Leverett J-function analysis
Mu, Yang (Petrochina Changqing Oilfield Corporation) | Castagna, John (University of Houston) | Bedle, Heather (University of Oklahoma)
ABSTRACT The integration of a Leverett J-function analysis with the Gassmann and mass-balance equations allows the time-lapse change of seismic reflectivity to be expressed explicitly in terms of the change of the free water-contact (WC) level, reservoir porosity, and initial water saturation. Given the initial 3D distribution of water saturation and porosity and a well-log derived height-saturation-porosity function as a hard inversion constraint, synthetic modeling suggests that time-lapse seismic data can potentially be directly inverted for the change in free-water level, and time-lapse changes in the spatial variation of water saturation can thus be predicted. This integrated inversion approach is applied to a real time-lapse seismic difference volume from the Maui-B field in the Taranaki Basin, New Zealand, where the change of WC level from a baseline model is the only free parameter to be inverted and is obtained by searching for the global error minimum between tmodeled and real time-lapse seismic differences as the modeled WC level is varied. The method correctly predicts the gas depletion and a measurable rise of the water contact on the southern flank of the field.
- Asia > China (0.93)
- North America > United States > Texas (0.93)
- Oceania > New Zealand > North Island > Tasman Sea (0.29)
- South America > Brazil > Campos Basin (0.99)
- Oceania > New Zealand > North Island > Tasman Sea > Taranaki Basin > Maui Field (0.99)
- Oceania > New Zealand > North Island > Taranaki Basin (0.99)
- (10 more...)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Seismic (four dimensional) monitoring (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Numerous AVO fluid indicators have been introduced and proven to be sensitive to hydrocarbon presence. Mathematically, fluid indicators measure the deviation of seismic responses of hydrocarbon-saturated reservoirs from their background in a specific domain. We introduce a new expression for the fluid factor commonly used in AVO analysis and interpretation. The expression is a function of common AVO intercept and gradient and a weighting coefficient that allows one to suppress the contribution of lithology and other factors not related to fluid content. The performance of the weighted fluid factor is compared with other fluid factor expressions using a worldwide collection of velocity measurements. A case study on the Northwest Shelf of Australia shows that the fluid factor successfully detects known pay intervals.
- Geology > Geological Subdiscipline (0.95)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.69)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.32)
- Oceania > Australia > Western Australia > Western Australia > Timor Sea > Browse Basin (0.99)
- Oceania > Australia > Western Australia > North West Shelf > Timor Sea > Browse Basin (0.99)
- Oceania > Australia > Western Australia > North West Shelf > Browse Basin > Scott Reef Trend > Block WA-398-P > Poseidon Field > Plover Formation (0.99)
- (4 more...)
Abstract Sparse reflectivity inversion of processed reflection seismic data is intended to produce reflection coefficients that represent boundaries between geologic layers. However, the objective function for sparse inversion is usually dominated by large reflection coefficients, which may result in unstable inversion for weak events, especially those interfering with strong reflections. We have determined that any seismogram can be decomposed according to the characteristics of the inverted reflection coefficients that can be sorted and subset by magnitude, sign, and sequence, and new seismic traces can be created from only reflection coefficients that pass the sorting criteria. We call this process reflectivity decomposition. For example, original inverted reflection coefficients can be decomposed by magnitude, large ones removed, the remaining reflection coefficients reconvolved with the wavelet, and this residual reinverted, thereby stabilizing inversions for the remaining weak events. As compared with inverting an original seismic trace, subtle impedance variations occurring in the vicinity of nearby strong reflections can be better revealed and characterized when only the events caused by small reflection coefficients are passed and reinverted. When we apply reflectivity decomposition to a 3D seismic data set in the Midland Basin, seismic inversion for weak events is stabilized such that previously obscured porous intervals in the original inversion can be detected and mapped, with a good correlation to the actual well logs.
- North America > United States > Texas (1.00)
- North America > United States > New Mexico (0.88)
- Geology > Rock Type > Sedimentary Rock (0.46)
- Geology > Geological Subdiscipline (0.46)
- Geology > Structural Geology > Tectonics (0.46)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation (0.93)
- Geophysics > Seismic Surveying > Surface Seismic Acquisition (0.86)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.34)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (25 more...)
- Information Technology > Data Science (0.46)
- Information Technology > Artificial Intelligence (0.46)
Abstract Sparse-layer reflectivity inversion decomposes a seismic trace into a limited number of simple layer responses and their corresponding reflection coefficients for top and base reflections. In contrast to sparse-spike inversion, the applied sparsity constraint is less biased against layer thickness and can thus better resolve thin subtuning layers. Application to a 3D seismic data set in Southern Alberta produces inverted impedances that have better temporal resolution and lateral stability and a less blocky appearance than sparse-spike inversion. Bandwidth extension harmonically extrapolated the frequency spectra of the inverted layers and nearly doubled the usable bandwidth. Although the prospective glauconitic sand tunes at approximately 37ย m, bandwidth extension reduced the tuning thickness to 22ย m. Bandwidth-extended data indicate a higher correlation with synthetic traces than the original seismic data and reveal features below the original tuning thickness. After bandwidth extension, the channel top and base are more evident on inline and crossline profiles. Lateral facies changes interpreted from the inverted acoustic impedance of the bandwidth-extended data are consistent with observations in wells.
- Geology > Geological Subdiscipline > Stratigraphy (0.89)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.70)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.87)
- North America > Canada > Alberta > Western Canada Sedimentary Basin > Alberta Basin > Upper Mannville Group Formation (0.99)
- North America > Canada > Alberta > Western Canada Sedimentary Basin > Alberta Basin > Leduc Field > Leduc Formation > Leduc Formation > Leduc D-3 Formation (0.99)
- North America > Canada > Alberta > Western Canada Sedimentary Basin > Alberta Basin > Leduc Field > Leduc Formation > Leduc D-2 Formation > Leduc D-3 Formation (0.99)
- (2 more...)
Case study: Seismic resolution and reservoir characterization of thin sands using multiattribute analysis and bandwidth extension in the Daqing field, China
Mora, David (University of Houston) | Castagna, John (University of Houston) | Meza, Ramses (BHP Billiton) | Chen, Shumin (Daqing Exploration and Development Research Institute) | Jiang, Renqi (New Horizons Ltd.)
Abstract The Daqing field, located in the Songliao Basin in northeastern China, is the largest oil field in China. Most production in the Daqing field comes from seismically thin sand bodies with thicknesses between 1 and 15ย m. Thus, it is not usually possible to resolve Daqing reservoirs using only conventional seismic data. We have evaluated the effectiveness of seismic multiattribute analysis of bandwidth extended data in resolving and making inferences about these thin layers. Multiattribute analysis uses statistical methods or neural networks to find relationships between well data and seismic attributes to predict some physical property of the earth. This multiattribute analysis was applied separately to conventional seismic data and seismic data that were spectrally broadened using sparse-layer inversion because this inversion method usually increases the vertical resolution of the seismic. Porosity volumes were generated using target porosity logs and conventional seismic attributes, and isofrequency volumes were obtained by spectral decomposition. The resulting resolution, statistical significance, and accuracy in the determination of layer properties were higher for the predictions made using the spectrally broadened volume.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Interpretation (1.00)
- Asia > China > Heilongjiang > Songliao Basin > Daqing Field > Yian Formation (0.99)
- Asia > China > Heilongjiang > Songliao Basin > Daqing Field > Mingshui Formation (0.99)
- North America > United States > Louisiana > China Field (0.97)
Introduction to special section: Rock properties from AVA/AVO analysis
Zhang, Zhao (Chevron) | Bao, Chen (Shell Exploration & Production Company) | Cardona, Reynaldo (Chevron) | Castagna, John (University of Houston) | Dygert, Todd (Chevron) | Mukerji, Tapan (Stanford University) | Gelinsky, Stephan (Shell Exploration & Production Company) | Russell, Brian (CGG GeoSoftware) | Sun, Yuefeng (Texas A&M University) | Xu, Shiyu (ExxonMobil Upstream Integrated Solutions)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.73)
ABSTRACT Conventional sparse-spike seismic inversion can have difficulty characterizing layers with weak reflectivity that are interfering with side-lobes from immediately overlying or underlying large reflection events. The inversion parameterizations and constraints are dominated by large reflections and may result in inversion instability for weak events that are "smothered"ย by the stronger reflections. Any seismogram can be decomposed according to the size of inverted reflection coefficients producing the seismogram. Reflection coefficients can be sorted by their magnitude and sign and new seismic traces can be created including only reflection coefficients within certain amplitude ranges. Large inverted reflection coefficients can be removed and the residual reinverted, thereby stabilizing inversions for the remaining weak events. By this reflectivity decomposition, subtle impedance variations occurring in the vicinity of nearby strong reflections can be revealed seismically. This approach is demonstrated on a 3D seismic dataset in the Midland basin. Amplitude maps for weak events are stabilized such that previously undetectable porous intervals can be detected, mapped, and correlated to well logs. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 1:50 PM Presentation Start Time: 3:30 PM Location: 217A Presentation Type: Oral
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.35)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (24 more...)
ABSTRACT Multi-attribute analysis utilizes statistical methods to find a relationship between well data and seismic attributes, to predict some physical property of the earth. Multi-attribute analysis was applied to both conventional seismic and spectrally-broadened seismic to resolve and make inferences about thin layers in the Daqing field, China. Porosity volumes were generated utilizing porosity logs from density logs, the attributes used were internal software attributes and externally generated spectral decomposition volumes. Resulting resolution, statistical significance, and accuracy in the determination of layer thickness and porosity were higher when using the spectrally-broadened volume as input to the multiattribute process. Presentation Date: Wednesday, October 17, 2018 Start Time: 9:20:00 AM Location: Poster Station 5 Presentation Type: Poster
- Geophysics > Seismic Surveying > Seismic Processing (0.70)
- Geophysics > Seismic Surveying > Seismic Interpretation (0.52)
- Asia > China > Heilongjiang > Songliao Basin > Daqing Field > Yian Formation (0.99)
- Asia > China > Heilongjiang > Songliao Basin > Daqing Field > Mingshui Formation (0.99)
The multiscale Fourier transform
Locci-Lopez, Daniel (School of Geosciences, University of Louisiana at Lafayette) | Zhang, Rui (School of Geosciences, University of Louisiana at Lafayette) | Oyem, Arnold (Department of Earth and Atmospheric Sciences, University of Houston) | Castagna, John (Department of Earth and Atmospheric Sciences, University of Houston)
ABSTRACT Multi-resolution spectral decomposition methods such as the S-transform and the Continuous Waelet Transform, are known to distort spectral attributes such as peak frequency. We introduce a spectral decomposition approach via a multi-scale Fourier Transform that utilizes a frequency-dependent temporal window to achieve any desired combination of temporal and frequency resolution. We investigate a specific frequency-dependent window that focusses the analysis on the full-width at half-maximum of a frequency-dependent Gaussian function. The resulting time-frequency analysis has significantly improved time-resolution relative to the S-transform. This is demonstrated on real seismic data in the Permian Basin. Presentation Date: Monday, October 15, 2018 Start Time: 1:50:00 PM Location: Poster Station 19 Presentation Type: Poster
- North America > United States > Texas (0.25)
- North America > United States > New Mexico (0.25)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (21 more...)