Discrimination between pressure and fluid saturation changes from marine multicomponent time‐lapse seismic data

Geophysics ◽  
2003 ◽  
Vol 68 (5) ◽  
pp. 1592-1599 ◽  
Author(s):  
Martin Landrø ◽  
Helene Hafslund Veire ◽  
Kenneth Duffaut ◽  
Nazih Najjar
Keyword(s):  
Pore Pressure ◽  
Seismic Data ◽  
Water Saturation ◽  
Synthetic Data ◽  
Time Lapse ◽  
Seismic Survey ◽  
Data Sets ◽  
Amplitude Variation With Offset ◽  
Fluid Saturation ◽  
Pressure Changes

Explicit expressions for computation of saturation and pressure‐related changes from marine multicomponent time‐lapse seismic data are presented. Necessary input is PP and PS stacked data for the baseline seismic survey and the repeat survey. Compared to earlier methods based on PP data only, this method is expected to be more robust since two independent measurements are used in the computation. Due to a lack of real marine multicomponent time‐lapse seismic data sets, the methodology is tested on synthetic data sets, illustrating strengths and weaknesses of the proposed technique. Testing ten scenarios for various changes in pore pressure and fluid saturation, we find that it is more robust for most cases to use the proposed 4D PP/PS technique instead of a 4D PP amplitude variation with offset (AVO) technique. The fit between estimated and “real” changes in water saturation and pore pressure were good for most cases. On the average, we find that the deviation in estimated saturation changes is 8% and 0.3 MPa for the estimated pore pressure changes. For PP AVO, we find that the corresponding average errors are 9% and 1.0 MPa. In the present method, only 4D PP and PS amplitude changes are used in the calculations. It is straightforward to include use of 4D traveltime shifts in the algorithm and, if reliable time shifts can be measured, this will most likely further stabilize the presented method.

Discrimination between pressure and fluid saturation changes from time‐lapse seismic data

Geophysics ◽  
2001 ◽  
Vol 66 (3) ◽  
pp. 836-844 ◽  
Author(s):  
Martin Landrø
Keyword(s):  
Seismic Data ◽  
Time Lapse ◽  
Seismic Survey ◽  
Baseline Survey ◽  
Water Contact ◽  
Data Set ◽  
Seismic Surveys ◽  
Fluid Saturation ◽  
Oil Water ◽  
Pressure Changes

Explicit expressions for computing saturation‐ and pressure‐related changes from time‐lapse seismic data have been derived and tested on a real time‐lapse seismic data set. Necessary input is near‐and far‐offset stacks for the baseline seismic survey and the repeat survey. The method has been tested successfully in a segment where pressure measurements in two wells verify a pore‐pressure increase of 5 to 6 MPa between the baseline survey and the monitor survey. Estimated pressure changes using the proposed relationships fit very well with observations. Between the baseline and monitor seismic surveys, 27% of the estimated recoverable hydrocarbon reserves were produced from this segment. The estimated saturation changes also agree well with observed changes, apart from some areas in the water zone that are mapped as being exposed to saturation changes (which is unlikely). Saturation changes in other segments close to the original oil‐water contact and the top reservoir interface are also estimated and confirmed by observations in various wells.

Stochastic inversion of pressure and saturation changes from time-lapse AVO data

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. C81-C92 ◽  
Author(s):  
Helene Hafslund Veire ◽  
Hilde Grude Borgos ◽  
Martin Landrø
Keyword(s):  
Stochastic Model ◽  
Seismic Data ◽  
Synthetic Data ◽  
Time Lapse ◽  
Bayesian Framework ◽  
Reservoir Modeling ◽  
Data Set ◽  
The North ◽  
Fluid Saturation ◽  
Likelihood Model

Effects of pressure and fluid saturation can have the same degree of impact on seismic amplitudes and differential traveltimes in the reservoir interval; thus, they are often inseparable by analysis of a single stacked seismic data set. In such cases, time-lapse AVO analysis offers an opportunity to discriminate between the two effects. We quantify the uncertainty in estimations to utilize information about pressure- and saturation-related changes in reservoir modeling and simulation. One way of analyzing uncertainties is to formulate the problem in a Bayesian framework. Here, the solution of the problem will be represented by a probability density function (PDF), providing estimations of uncertainties as well as direct estimations of the properties. A stochastic model for estimation of pressure and saturation changes from time-lapse seismic AVO data is investigated within a Bayesian framework. Well-known rock physical relationships are used to set up a prior stochastic model. PP reflection coefficient differences are used to establish a likelihood model for linking reservoir variables and time-lapse seismic data. The methodology incorporates correlation between different variables of the model as well as spatial dependencies for each of the variables. In addition, information about possible bottlenecks causing large uncertainties in the estimations can be identified through sensitivity analysis of the system. The method has been tested on 1D synthetic data and on field time-lapse seismic AVO data from the Gullfaks Field in the North Sea.

Fluid-pressure discrimination in anisotropic reservoir rocks — A sensitivity study

Geophysics ◽  
2005 ◽  
Vol 70 (3) ◽  
pp. O1-O11 ◽  
Author(s):  
Alexey Stovas ◽  
Martin Landrø
Keyword(s):  
Pore Pressure ◽  
Seismic Data ◽  
Seismic Anisotropy ◽  
Fluid Pressure ◽  
Rock Physics ◽  
Time Lapse ◽  
Reservoir Rock ◽  
Sand Layer ◽  
Weak Anisotropy ◽  
Fluid Saturation

We investigate how seismic anisotropy influences our ability to distinguish between various production-related effects from time-lapse seismic data. Based on rock physics models and ultrasonic core measurements, we estimate variations in PP and PS reflectivity at the top reservoir interface for fluid saturation and pore pressure changes. The tested scenarios include isotropic shale, weak anisotropic shale, and highly anisotropic shale layers overlaying either an isotropic reservoir sand layer or a weak anisotropic sand layer. We find that, for transverse isotropic media with a vertical symmetry axis (TIV), the effect of weak anisotropy in the cap rock does not lead to significant errors in, for instance, the simultaneous determination of pore-pressure and fluid-saturation changes. On the other hand, changes in seismic anisotropy within the reservoir rock (caused by, for instance, increased fracturing) might be detectable from time-lapse seismic data. A new method using exact expressions for PP and PS reflectivity, including TIV anisotropy, is used to determine pressure and saturation changes over production time. This method is assumed to be more accurate than previous methods.

Time-lapse seismic data registration and inversion for CO2 sequestration study at Cranfield

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. B329-B338 ◽  
Author(s):  
Rui Zhang ◽  
Xiaolei Song ◽  
Sergey Fomel ◽  
Mrinal K. Sen ◽  
Sanjay Srinivasan
Keyword(s):  
Cross Sections ◽  
Seismic Data ◽  
Time Lapse ◽  
Seismic Survey ◽  
Rock Properties ◽  
Time Shift ◽  
Data Sets ◽  
Registration Method ◽  
Data Registration ◽  
Seismic Amplitude

The time-lapse seismic survey for [Formula: see text] sequestration study at Cranfield can be problematic because of misalignments between time-lapse data sets. Such misalignments can be caused by the seismic data processing workflow and may result in the wrong interpretation of time-lapse seismic amplitude differences. We propose an efficient local-correlation-based warping method of registering the time-lapse poststack data sets, which can align these data sets without changing original amplitudes. Application of our registration method to Cranfield time-lapse data demonstrates its effectiveness in separating time-shift character from seismic amplitude signature. After registration, time-lapse differences show an improved consistency in vertical cross sections and a more localized distribution of difference amplitudes along the horizon, allowing us to apply a high-resolution basis pursuit inversion (BPI) for acoustic impedances. Inversion results show that decreases in acoustic impedances occur mostly at the top of the injection interval, which can be used as an indicator of rock properties to detect a subsurface [Formula: see text] plume.

Sparse reflectivity inversion for nonstationary seismic data with surface-related multiples: Numerical and field-data experiments

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. R199-R217 ◽  
Author(s):  
Xintao Chai ◽  
Shangxu Wang ◽  
Genyang Tang
Keyword(s):  
Seismic Data ◽  
Resolution Enhancement ◽  
Synthetic Data ◽  
Data Sets ◽  
Data Set ◽  
Anelastic Attenuation ◽  
Seismic Resolution ◽  
Text Filtering ◽  
The Stability ◽  
Reflectivity Inversion

Seismic data are nonstationary due to subsurface anelastic attenuation and dispersion effects. These effects, also referred to as the earth’s [Formula: see text]-filtering effects, can diminish seismic resolution. We previously developed a method of nonstationary sparse reflectivity inversion (NSRI) for resolution enhancement, which avoids the intrinsic instability associated with inverse [Formula: see text] filtering and generates superior [Formula: see text] compensation results. Applying NSRI to data sets that contain multiples (addressing surface-related multiples only) requires a demultiple preprocessing step because NSRI cannot distinguish primaries from multiples and will treat them as interference convolved with incorrect [Formula: see text] values. However, multiples contain information about subsurface properties. To use information carried by multiples, with the feedback model and NSRI theory, we adapt NSRI to the context of nonstationary seismic data with surface-related multiples. Consequently, not only are the benefits of NSRI (e.g., circumventing the intrinsic instability associated with inverse [Formula: see text] filtering) extended, but also multiples are considered. Our method is limited to be a 1D implementation. Theoretical and numerical analyses verify that given a wavelet, the input [Formula: see text] values primarily affect the inverted reflectivities and exert little effect on the estimated multiples; i.e., multiple estimation need not consider [Formula: see text] filtering effects explicitly. However, there are benefits for NSRI considering multiples. The periodicity and amplitude of the multiples imply the position of the reflectivities and amplitude of the wavelet. Multiples assist in overcoming scaling and shifting ambiguities of conventional problems in which multiples are not considered. Experiments using a 1D algorithm on a synthetic data set, the publicly available Pluto 1.5 data set, and a marine data set support the aforementioned findings and reveal the stability, capabilities, and limitations of the proposed method.

scholarly journals Time-Lapse Seismic Monitoring of Onshore Reservoirs in Niger Delta, Field ‘K’ as a Case Study

2017 ◽  
Vol 1 (1) ◽  
pp. 23-27 ◽  
Author(s):  
A. Ogbamikhumi ◽  
T. Tralagba ◽  
E. E. Osagiede
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Niger Delta ◽  
Rock Physics ◽  
Time Lapse ◽  
Seismic Survey ◽  
Impedance Change ◽  
Data Set ◽  
Reservoir Fluid ◽  
4D Seismic

Field ‘K’ is a mature field in the coastal swamp onshore Niger delta, which has been producing since 1960. As a huge producing field with some potential for further sustainable production, field monitoring is therefore important in the identification of areas of unproduced hydrocarbon. This can be achieved by comparing production data with the corresponding changes in acoustic impedance observed in the maps generated from base survey (initial 3D seismic) and monitor seismic survey (4D seismic) across the field. This will enable the 4D seismic data set to be used for mapping reservoir details such as advancing water front and un-swept zones. The availability of good quality onshore time-lapse seismic data for Field ‘K’ acquired in 1987 and 2002 provided the opportunity to evaluate the effect of changes in reservoir fluid saturations on time-lapse amplitudes. Rock physics modelling and fluid substitution studies on well logs were carried out, and acoustic impedance change in the reservoir was estimated to be in the range of 0.25% to about 8%. Changes in reservoir fluid saturations were confirmed with time-lapse amplitudes within the crest area of the reservoir structure where reservoir porosity is 0.25%. In this paper, we demonstrated the use of repeat Seismic to delineate swept zones and areas hit with water override in a producing onshore reservoir.

Common-focus point-based target-oriented imaging approach for continuous seismic reservoir monitoring

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. M41-M48 ◽  
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Time Lapse ◽  
Velocity Estimation ◽  
Estimation Methods ◽  
Data Sets ◽  
Data Set ◽  
Velocity Models ◽  
Reservoir Monitoring ◽  
Focus Point

The ideal approach for continuous reservoir monitoring allows generation of fast and accurate images to cope with the massive data sets acquired for such a task. Conventionally, rigorous depth-oriented velocity-estimation methods are performed to produce sufficiently accurate velocity models. Unlike the traditional way, the target-oriented imaging technology based on the common-focus point (CFP) theory can be an alternative for continuous reservoir monitoring. The solution is based on a robust data-driven iterative operator updating strategy without deriving a detailed velocity model. The same focusing operator is applied on successive 3D seismic data sets for the first time to generate efficient and accurate 4D target-oriented seismic stacked images from time-lapse field seismic data sets acquired in a [Formula: see text] injection project in Saudi Arabia. Using the focusing operator, target-oriented prestack angle domain common-image gathers (ADCIGs) could be derived to perform amplitude-versus-angle analysis. To preserve the amplitude information in the ADCIGs, an amplitude-balancing factor is applied by embedding a synthetic data set using the real acquisition geometry to remove the geometry imprint artifact. Applying the CFP-based target-oriented imaging to time-lapse data sets revealed changes at the reservoir level in the poststack and prestack time-lapse signals, which is consistent with the [Formula: see text] injection history and rock physics.

Signal leakage in f-x deconvolution algorithms

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. W31-W45 ◽  
Author(s):  
Necati Gülünay
Keyword(s):  
Field Data ◽  
New Technologies ◽  
Filter Design ◽  
Synthetic Data ◽  
Data Sets ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Backward Design ◽  
Use Of Data ◽  
Domain Prediction

The old technology [Formula: see text]-[Formula: see text] deconvolution stands for [Formula: see text]-[Formula: see text] domain prediction filtering. Early versions of it are known to create signal leakage during their application. There have been recent papers in geophysical publications comparing [Formula: see text]-[Formula: see text] deconvolution results with the new technologies being proposed. These comparisons will be most effective if the best existing [Formula: see text]-[Formula: see text] deconvolution algorithms are used. This paper describes common [Formula: see text]-[Formula: see text] deconvolution algorithms and studies signal leakage occurring during their application on simple models, which will hopefully provide a benchmark for the readers in choosing [Formula: see text]-[Formula: see text] algorithms for comparison. The [Formula: see text]-[Formula: see text] deconvolution algorithms can be classified by their use of data which lead to transient or transient-free matrices and hence windowed or nonwindowed autocorrelations, respectively. They can also be classified by the direction they are predicting: forward design and apply; forward design and apply followed by backward design and apply; forward design and apply followed by application of a conjugated forward filter in the backward direction; and simultaneously forward and backward design and apply, which is known as noncausal filter design. All of the algorithm types mentioned above are tested, and the results of their analysis are provided in this paper on noise free and noisy synthetic data sets: a single dipping event, a single dipping event with a simple amplitude variation with offset, and three dipping events. Finally, the results of applying the selected algorithms on field data are provided.

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