Improved seismic inversion and reservoir description of the Ichthys gas-condensate field, Browse Basin, Western Australia

2010 ◽  
Vol 50 (2) ◽  
pp. 716
Author(s):  
Masamichi Fujimoto ◽  
Takeshi Yoshida ◽  
Andrew Long
Keyword(s):  
Low Frequency ◽  
Seismic Inversion ◽  
Gas Condensate ◽  
Sensor Technology ◽  
Frequency Model ◽  
Porosity Distribution ◽  
Low Frequencies ◽  
Simultaneous Inversion ◽  
Dual Sensor ◽  
Well Data

Seismic inversion has become a standard geophysical tool to enhance seismic resolution, predict the reservoir porosity distribution, and to discriminate between reservoir and non-reservoir pay zones. Conventional seismic data does not record the low frequencies necessary for inversion. To enable a complete bandwidth, low frequencies are modelled from well data and are typically interpolated throughout the volume using seismic velocities. This often causes the resultant porosity distribution calculated from the inverted P-impedance to be biased by the well data and the geometry of well locations. Dual-sensor GeoStreamer technology was used to acquire a regional multi-client 2D survey by PGS in 2008, including some lines over the Ichthys gas-condensate field in the Browse Basin. Dual-sensor streamer processing recovers a wider frequency bandwidth than conventional seismic. Receiver ghost removal combined with deep streamer towing simultaneously boosts both the low and high frequencies. The improved bandwidth enables a higher quality of velocity analysis, which further improves resolution throughout the section. Simultaneous inversion of the data validated the uplift of the low frequency data, and significantly reduced the bias towards well data for the low frequency model. The resultant P-impedance data demonstrated an excellent tie to well data. The dual-sensor technology promises to improve the description of the porosity distribution within our reservoir model.

Accuracy of wavelets, seismic inversion, and thin-bed resolution

2017 ◽  
Vol 5 (4) ◽  
pp. T523-T530
Author(s):  
Ehsan Zabihi Naeini ◽  
Mark Sams
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Frequency Content ◽  
Frequency Model ◽  
North West ◽  
The North ◽  
Well Data

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.

Prediction of Petrophysical Properties from Seismic Inversion and Neural Network: A case study

2021 ◽  
Author(s):  
Siddharth Garia ◽  
Arnab Kumar Pal ◽  
Karangat Ravi ◽  
Archana M Nair
Keyword(s):  
Neural Network ◽  
Bulk Density ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Well Log ◽  
Petrophysical Properties ◽  
Seismic Section ◽  
Frequency Model ◽  
Seismic Reflection Data ◽  
Reflection Data

<p>Seismic inversion method is widely used to characterize reservoirs and detect zones of interest, i.e., hydrocarbon-bearing zone in the subsurface by transforming seismic reflection data into quantitative subsurface rock properties. The primary aim of seismic inversion is to transform the 3D seismic section/cube into an acoustic impedance (AI) cube. The integration of this elastic attribute, i.e., AI cube with well log data, can thereafter help to establish correlations between AI and different petrophysical properties. The seismic inversion algorithm interpolates and spatially populates data/parameters of wells to the entire seismic section/cube based on the well log information. The case study presented here uses machine learning-neural network based algorithm to extract the different petrophysical properties such as porosity and bulk density from the seismic data of the Upper Assam basin, India. We analyzed three different stratigraphic  units that are established to be producing zones in this basin.</p><p> AI model is generated from the seismic reflection data with the help of colored inversion operator. Subsequently, low-frequency model is generated from the impedance data extracted from the well log information. To compensate for the band limited nature of the seismic data, this low-frequency model is added to the existing acoustic model. Thereafter, a feed-forward neural network (NN) is trained with AI as input and porosity/bulk density as target, validated with NN generated porosity/bulk density with actual porosity/bulk density from well log data. The trained network is thus tested over the entire region of interest to populate these petrophysical properties.</p><p>Three seismic zones were identified from the seismic section ranging from 681 to 1333 ms, 1528 to 1575 ms and 1771 to 1814 ms. The range of AI, porosity and bulk density were observed to be 1738 to 6000 (g/cc) * (m/s), 26 to 38% and 1.95 to 2.46 g/cc respectively. Studies conducted by researchers in the same basin yielded porosity results in the range of 10-36%. The changes in acoustic impedance, porosity and bulk density may be attributed to the changes in lithology. NN method was prioritized over other traditional statistical methods due to its ability to model any arbitrary dependency (non-linear relationships between input and target values) and also overfitting can be avoided. Hence, the workflow presented here provides an estimation of reservoir properties and is considered useful in predicting petrophysical properties for reservoir characterization, thus helping to estimate reservoir productivity.</p>

The Great Australian Bight – from AVO prospectivity screening to potentially drillable targets in one of the world's remaining untapped basins

2017 ◽  
Vol 57 (2) ◽  
pp. 793
Author(s):  
Dushyan Rajeswaran ◽  
Marcin Przywara
Keyword(s):  
Low Frequency ◽  
Structural Complexity ◽  
Source Rocks ◽  
High Definition ◽  
Depth Migration ◽  
Velocity Models ◽  
Structural Style ◽  
Petroleum Resource ◽  
Dual Sensor ◽  
Well Data

The Ceduna Sub-basin in Australia’s southern margin offers an untapped opportunity for significant petroleum resource as part of the global exploration portfolio. Analogous to the prolific Niger delta in both size and structural style, this highly-extensional province contains up to 15 km of largely untested post-rift sediments including two widespread Late Cretaceous deltas linked to world-class oil-prone marine Cretaceous source rocks. Regional interpretation of legacy 2D seismic across the Bight Basin brings the sheer scale and structural complexity of this giant Cretaceous depocentre into perspective, but it is only through the detailed analysis of 8001 km2 of dual-sensor towed streamer 3D seismic that its true potential can be quantified. Rigorous phase and amplitude AVO QC of the pre-stack information, coupled with optimised velocity models fed into the depth migration sequence, have ensured amplitude fidelity and phase stability across all offset ranges. This has enabled a systematic and robust exploration workflow of AVO analysis and pre-stack inversion despite limited well data. Numerous dual-sensor case studies have nevertheless demonstrated these Relative Acoustic Impedance and Vp/Vs volumes to be reliably robust for prospect de-risking because of the extended low frequency bandwidth. Frontier screening supported by a partially-automated high-resolution stratigraphic framework has led to the identification of numerous prospects at multiple stratigraphic levels across the survey area. This includes isolation of laterally extensive and vertically amalgamated fan-like structures within the shallow Hammerhead delta using horizon-constrained high-definition spectral decomposition, and the extraction of potential AVO anomalies within the deeper structurally-controlled White Pointer sands draped across large gravity-driven listric growth faults.

Reservoir Prediction Under Control of Sedimentary Facies

2017 ◽  
Vol 25 (03) ◽  
pp. 1750022
Author(s):  
Xiuwei Yang ◽  
Peimin Zhu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Prediction Method ◽  
Rock Physics ◽  
Real Data ◽  
Sedimentary Facies ◽  
Seismic Inversion ◽  
Rock Properties ◽  
Reservoir Prediction ◽  
Frequency Model

Acoustic impedance (AI) from seismic inversion can indicate rock properties and can be used, when combined with rock physics, to predict reservoir parameters, such as porosity. Solutions to seismic inversion problem are almost nonunique due to the limited bandwidth of seismic data. Additional constraints from well log data and geology are needed to arrive at a reasonable solution. In this paper, sedimentary facies is used to reduce the uncertainty in inversion and rock physics modeling; the results not only agree with seismic data, but also conform to geology. A reservoir prediction method, which incorporates seismic data, well logs, rock physics and sedimentary facies, is proposed. AI was first derived by constrained sparse spike inversion (CSSI) using a sedimentary facies dependent low-frequency model, and then was transformed to reservoir parameters by sequential simulation, statistical rock physics and [Formula: see text]-model. Two numerical experiments using synthetic model and real data indicated that the sedimentary facies information may help to obtain a more reasonable prediction.

Interpretation of full-azimuth broadband land data from Saudi Arabia and implications for improved inversion, reservoir characterization, and exploration

2013 ◽  
Vol 1 (2) ◽  
pp. T167-T176 ◽  
Author(s):  
Brian P. Wallick ◽  
Luis Giroldi
Keyword(s):  
Saudi Arabia ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Gas Field ◽  
Frequency Model ◽  
Low Frequencies ◽  
Limited Bandwidth

Interpretation of conventional land seismic data over a Permian-age gas field in Eastern Saudi Arabia has proven difficult over time due to low signal-to-noise ratio and limited bandwidth in the seismic volume. In an effort to improve the signal and broaden the bandwidth, newly acquired seismic data over this field have employed point receiver technology, dense wavefield sampling, a full azimuth geometry, and a specially designed sweep with useful frequencies as low as three hertz. The resulting data display enhanced reflection continuity and improved resolution. With the extension of low frequencies and improved interpretability, acoustic impedance inversion results are more robust and allow greater flexibility in reservoir characterization and prediction. In addition, because inversion to acoustic impedance is no longer completely tied to a wells-only low-frequency model, there are positive implications for exploration.

Quantitative interpretation using facies-based seismic inversion

2017 ◽  
Vol 5 (3) ◽  
pp. SL1-SL8 ◽  
Author(s):  
Ehsan Zabihi Naeini ◽  
Russell Exley
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Quantitative Interpretation ◽  
Frequency Model ◽  
Amplitude Variation With Offset ◽  
Limited Bandwidth ◽  
Seismic Amplitude ◽  
Primary Signal

Quantitative interpretation (QI) is an important part of successful exploration, appraisal, and development activities. Seismic amplitude variation with offset (AVO) provides the primary signal for the vast majority of QI studies allowing the determination of elastic properties from which facies can be determined. Unfortunately, many established AVO-based seismic inversion algorithms are hindered by not fully accounting for inherent subsurface facies variations and also by requiring the addition of a preconceived low-frequency model to supplement the limited bandwidth of the input seismic. We apply a novel joint impedance and facies inversion applied to a North Sea prospect using broadband seismic data. The focus was to demonstrate the significant advantages of inverting for each facies individually and iteratively determine an optimized low-frequency model from facies-derived depth trends. The results generated several scenarios for potential facies distributions thereby providing guidance to future appraisal and development decisions.

Seismic inversion of a carbonate buildup: A case study

2017 ◽  
Vol 5 (4) ◽  
pp. T641-T652 ◽  
Author(s):  
Mark Sams ◽  
Paul Begg ◽  
Timur Manapov
Keyword(s):  
Seismic Data ◽  
Probability Distributions ◽  
Low Frequency ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Accurate Estimation ◽  
Amplitude Analysis ◽  
Simultaneous Inversion ◽  
Band Limited ◽  
Using Data

The information within seismic data is band limited and angle limited. Together with the particular physics and geology of carbonate rocks, this imposes limitations on how accurately we can predict the presence of hydrocarbons in carbonates, map the top carbonate, and characterize the porosity distribution through seismic amplitude analysis. Using data for a carbonate reef from the Nam Con Son Basin, Vietnam, the expectations based on rock-physics analysis are that the presence of gas can be predicted only when the porosity at the top of the carbonate is extremely high ([Formula: see text]), but that a fluid contact is unlikely to be observed in the background of significant porosity variations. Mapping the top of the carbonate (except when the top carbonate porosities are low) or a fluid contact requires accurate estimates of changes in [Formula: see text]. The seismic data do not independently support such an accurate estimation of sharp changes in [Formula: see text]. The standard approach of introducing low-frequency models and applying rock-physics constraints during a simultaneous inversion does not resolve the problems: The results are heavily biased by the well control and the initial interpretation of the top carbonate and fluid contact. A facies-based inversion in which the elastic properties are restricted to values consistent with the facies predicted to be present removes the well bias, but it does not completely obviate the need for a reasonably accurate initial interpretation in terms of prior facies probability distributions. Prestack inversion improves the quality of the facies predictions compared with a poststack inversion.

Stuck between a rock and a reflection: A tutorial on low-frequency models for seismic inversion

2017 ◽  
Vol 5 (2) ◽  
pp. B17-B27 ◽  
Author(s):  
Mark Sams ◽  
David Carter
Keyword(s):  
Elastic Properties ◽  
Model Building ◽  
Seismic Velocity ◽  
Low Frequency ◽  
Rock Physics ◽  
Frequency Component ◽  
Seismic Inversion ◽  
Rock Properties ◽  
Seismic Velocities ◽  
Frequency Model

Predicting the low-frequency component to be used for seismic inversion to absolute elastic rock properties is often problematic. The most common technique is to interpolate well data within a structural framework. This workflow is very often not appropriate because it is too dependent on the number and distribution of wells and the interpolation algorithm chosen. The inclusion of seismic velocity information can reduce prediction error, but it more often introduces additional uncertainties because seismic velocities are often unreliable and require conditioning, calibration to wells, and conversion to S-velocity and density. Alternative techniques exist that rely on the information from within the seismic bandwidth to predict the variations below the seismic bandwidth; for example, using an interpretation of relative properties to update the low-frequency model. Such methods can provide improved predictions, especially when constrained by a conceptual geologic model and known rock-physics relationships, but they clearly have limitations. On the other hand, interpretation of relative elastic properties can be equally challenging and therefore interpreters may find themselves stuck — unsure how to interpret relative properties and seemingly unable to construct a useful low-frequency model. There is no immediate solution to this dilemma; however, it is clear that low-frequency models should not be a fixed input to seismic inversion, but low-frequency model building should be considered as a means to interpret relative elastic properties from inversion.

scholarly journals Assessment of updated low frequency model in delineating bypassed hydrocarbon reservoir: A 4D seismic study of ’X’ - field, offshore, Niger Delta, Nigeria

2020 ◽  
Vol 13 (36) ◽  
pp. 3738-3753 ◽  
Author(s):  
Aniefiok Sylvester Akpan ◽  
Keyword(s):  
Acoustic Impedance ◽  
Deterministic Model ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Fluid Replacement ◽  
Inversion Method ◽  
Frequency Model ◽  
Hydrocarbon Reservoir ◽  
Model Based ◽  
4D Seismic

Aim/objectives: The aim of this research is, to use Time lapse (4D) seismic and investigate the influence of low frequency update in deterministic model-based seismic inversion employed in delineating a prospect saturated with bypassed hydrocarbon accumulation. Method: The dataset employed in this study incorporates 4D seismic volumes with fifteen (15) years production, interval between 2001 baseline and 2016 monitor seismic vintages. The inversion was carried out using full bandwidth of the updated low frequency and bandpass filtered low frequency approaches. The seismic vintages (baseline and monitor) were simultaneously inverted into acoustic impedance volumes for the two approaches. The formation fluid and lithology were discriminated through fluid replacement modelling (FRM) based on the colour separation between brine and gas saturation scenarios. Findings: The two inversion methods employed reveal six (6) zones suspected to be saturated with bypassed hydrocarbons. The delineated bypassed zones are masked in the full bandwidth approach,depicting the effect of the updated low frequency model. Meanwhile, the bandpass filtered approach result presents a better delineated bypassed reservoir as the zones are more pronounced when compared with the full bandwidth approach. Porosity estimate reveals that the bandpass filtered approach is characterized with excellent porosity in the suspected bypassed zones. The results equally gave more reliable and full delineated bypassed zones. Originality and novelty: The dataset employed in this study were obtained from a producing hydrocarbon field which, interest is to maximize the production of oil/gas. The study will bridge the inherent gab observed in using model-based seismic inversion approach to analyse and interpret seismic data in order to delineate hydrocarbon prospects. The research reveals that,the model-based seismic inversion method is still very effective in delineating hydrocarbon prospect when the updated low frequency is bandpass filtered to remove the model effect which influences the inverted acoustic impedance results. Keywords: Porosity; frequency; bypassed; reservoir and impedance

scholarly journals Predicting the Depositional Environments of Mishrif Formation from Seismic Isopach Map in the Dujaila Oil Field, Southeast-Iraq

2021 ◽  
pp. 1943-1955
Author(s):  
Ahmed Muslim Khawaja ◽  
Jassim Muhammad Thabit
Keyword(s):  
Low Frequency ◽  
Depositional Environments ◽  
Oil Field ◽  
Frequency Model ◽  
Environment Model ◽  
Carbonate Formation ◽  
Porous Reservoir ◽  
Well Data ◽  
Isopach Map ◽  
Marine Basin

In this paper, we attempt to predict the depositional environments with associated lithofacies of the main reservoir of the late Cretaceous Mishrif carbonate Formation, depending on the analysis of the created seismic isopach map by integrating seismic and well data. The isopach map was created from a 3D-seismic reflection survey carried out at the Dujaila oil field in southeastern Iraq, which is of an area of 602.26 Km2, and integrated with the data of the two explored wells. Based on the interpretation of the seismic isopach map, the diagram of the 3D-depositional environment model of Mishrif Formation was constructed. It showed three distinguished depositional environments, which were graduated from a back reef lithofacies of a shallow open marine (shelf) environment in the west and NW, to a shoal environment of isolated Rudist reefal buildup in the middle, and a fore reef lithofacies of the deep open marine basin environment in the SE of the field. A 3D-instantaneous frequency model was generated to verify the capability of the seismic isopach map of predicting the depositional environments, which in turn showed that the low frequency was restricted in the region of the high thickness of Rudist reefal buildups (porous reservoir facies) in the vicinity of the productive well Dujaila-1.

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