Pore-pressure detection sensitivities tested with time-lapse seismic data

Geophysics ◽  
2005 ◽  
Vol 70 (6) ◽  
pp. O39-O50 ◽  
Author(s):  
Øyvind Kvam ◽  
Martin Landrø
Keyword(s):  
Pore Pressure ◽  
Seismic Data ◽  
Time Lapse ◽  
Pressure Increase ◽  
Burial Depth ◽  
Velocity Analysis ◽  
Seismic Velocities ◽  
Data Set ◽  
Pore Pressure Prediction ◽  
Velocity Changes

In an exploration context, pore-pressure prediction from seismic data relies on the fact that seismic velocities depend on pore pressure. Conventional velocity analysis is a tool that may form the basis for obtaining interval velocities for this purpose. However, velocity analysis is inaccurate, and in this paper we focus on the possibilities and limitations of using velocity analysis for pore-pressure prediction. A time-lapse seismic data set from a segment that has undergone a pore-pressure increase of 5 to 7 MPa between the two surveys is analyzed for velocity changes using detailed velocity analysis. A synthetic time-lapse survey is used to test the sensitivity of the velocity analysis with respect to noise. The analysis shows that the pore-pressure increase cannot be detected by conventional velocity analysis because the uncertainty is much greater than the expected velocity change for a reservoir of the given thickness and burial depth. Finally, by applying amplitude-variation-with-offset (AVO) analysis to the same data, we demonstrate that seismic amplitude analysis may yield more precise information about velocity changes than velocity analysis.

Quantitative estimation of compaction and velocity changes using 4D impedance and traveltime changes

Geophysics ◽  
2004 ◽  
Vol 69 (4) ◽  
pp. 949-957 ◽  
Author(s):  
Martin Landrø ◽  
Jan Stammeijer
Keyword(s):  
Seismic Data ◽  
Quantitative Estimation ◽  
Time Lapse ◽  
Seismic Velocities ◽  
Compaction Process ◽  
Empirical Relationships ◽  
Velocity Change ◽  
Reservoir Rocks ◽  
Velocity Changes ◽  
4D Seismic

In some hydrocarbon reservoirs, severe compaction of the reservoir rocks is observed. This compaction is caused by production, and it is often associated with changes in the overburden. Time‐lapse (or 4D) seismic data are used to monitor this compaction process. Since the compaction causes changes in both layer thickness and seismic velocities, it is crucial to distinguish between the two effects. Two new seismic methods for monitoring compacting reservoirs are introduced, one based on measured seismic prestack traveltime changes, and the other based on poststack traveltime and amplitude changes. In contrast to earlier methods, these methods do not require additional empirical relationships, such as, for instance, a velocity‐porosity relationship. The uncertainties in estimates for compaction and velocity change are expressed in terms of errors in the traveltime and amplitude measurements. These errors are directly related to the quality and repeatability of time‐lapse seismic data. For a reservoir at 3000‐m depth with 9 m of compaction, and assuming a 4D timeshift error of 0.5 ms at near offset and 2 ms at far offset, we find relative uncertainty in the compaction estimate of approximately 50–60% using traveltime information only.

Predrill pore‐pressure prediction using seismic data

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1286-1292 ◽  
Author(s):  
C. M. Sayers ◽  
G. M. Johnson ◽  
G. Denyer
Keyword(s):  
Velocity Field ◽  
Gulf Of Mexico ◽  
Pore Pressure ◽  
Seismic Data ◽  
Seismic Velocities ◽  
Pressure Data ◽  
Pore Pressure Prediction ◽  
Well Data ◽  
Interval Velocities ◽  
Reflection Tomography

1A predrill estimate of pore pressure can be obtained from seismic velocities using a velocity‐to–pore‐pressure transform, but the seismic velocities need to be derived using methods having sufficient resolution for well planning purposes. For a deepwater Gulf of Mexico example, significant differences are found between the velocity field obtained using reflection tomography and that obtained using a conventional method based on the Dix equation. These lead to significant differences in the predicted pore pressure. Parameters in the velocity‐to–pore‐pressure transform are estimated using seismic interval velocities and pressure data from nearby calibration wells. The uncertainty in the pore pressure prediction is analyzed by examining the spread in the predicted pore pressure obtained using parameter combinations which sample the region of parameter space consistent with the available well data. If calibration wells are not available, the ideas proposed in this paper can be used with measurements made while drilling to predict pore pressure ahead of the bit based on seismic velocities.

Estimation of layer thickness and velocity changes using 4D prestack seismic data

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. S219-S234 ◽  
Author(s):  
Thomas Røste ◽  
Alexey Stovas ◽  
Martin Landrø
Keyword(s):  
Layer Thickness ◽  
Seismic Data ◽  
Single Layer ◽  
Time Lapse ◽  
Seismic Velocities ◽  
Seismic Line ◽  
Velocity Increase ◽  
Reservoir Compaction ◽  
Velocity Changes ◽  
Zero Offset

In some hydrocarbon reservoirs, severe compaction of the reservoir rocks is observed. This compaction is caused by production and is often associated with stretching and arching of the overburden rocks. Time-lapse seismic data can be used to monitor these processes. Since compaction and stretching cause changes in layer thickness as well as seismic velocities, it is crucial to develop methods to distinguish between the two effects. We introduce a new method based on detailed analysis of time-lapse prestack seismic data. The equations are derived assuming that the entire model consists of only one single layer with no vertical velocity variations. The method incorporates lateral variations in (relative) velocity changes by utilizing zero-offset and offset-dependent time shifts. To test the method, we design a 2D synthetic model that undergoes severe reservoir compaction as well as stretching of the overburden rocks. Finally, we utilize the method to analyze a real 2D prestack time-lapse seismic line from the Valhall field, acquired in 1992 and 2002. For a horizon at a depth of around [Formula: see text], which is near the top reservoir horizon, a subsidence of [Formula: see text] and a velocity decrease of [Formula: see text] for the sequence from the sea surface to the top reservoir horizon are estimated. By assuming that the base of the reservoir remains constant in depth, a reservoir compaction of 3.6% (corresponding to a subsidence of the top reservoir horizon of [Formula: see text]) and a corresponding reservoir velocity increase of 6.7% (corresponding to a velocity increase of [Formula: see text]) are estimated.

scholarly journals Physics-Based Relationship for Pore Pressure and Vertical Stress Monitoring Using Seismic Velocity Variations

2021 ◽  
Vol 13 (14) ◽  
pp. 2684
Author(s):  
Eldert Fokker ◽  
Elmer Ruigrok ◽  
Rhys Hawkins ◽  
Jeannot Trampert
Keyword(s):  
Pore Pressure ◽  
Seismic Velocity ◽  
Pressure Head ◽  
Groundwater Table ◽  
Surface Velocity ◽  
Seismic Velocities ◽  
Stress Monitoring ◽  
Near Surface ◽  
Velocity Variations ◽  
Velocity Changes

Previous studies examining the relationship between the groundwater table and seismic velocities have been guided by empirical relationships only. Here, we develop a physics-based model relating fluctuations in groundwater table and pore pressure with seismic velocity variations through changes in effective stress. This model justifies the use of seismic velocity variations for monitoring of the pore pressure. Using a subset of the Groningen seismic network, near-surface velocity changes are estimated over a four-year period, using passive image interferometry. The same velocity changes are predicted by applying the newly derived theory to pressure-head recordings. It is demonstrated that the theory provides a close match of the observed seismic velocity changes.

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.

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.

Pore Pressure Prediction in Sandstone Using a Lateral Transfer Approach

2021 ◽  
Author(s):  
Jose Francisco Consuegra
Keyword(s):  
Pore Pressure ◽  
Seismic Data ◽  
Strong Relationship ◽  
Lateral Transfer ◽  
Earth Model ◽  
Driving Mechanism ◽  
Shale Formations ◽  
Sand Body ◽  
Pore Pressure Prediction ◽  
Normal Trend

Abstract Accurate pore pressure prediction is required to determine reliable static mud weights and circulating pressures, necessary to mitigate the risk of influx, blowouts and borehole instability. To accurately estimate the pore pressure, the over-pressure mechanism has to be identified with respect to the geological environment. One of the most widely used methods for pore pressure prediction is based on Normal Compaction Trend Analysis, where the difference between a ‘normal trend' and log value of a porosity indicator log such as sonic or resistivity is used to estimate the pore pressure. This method is biased towards shales, which typically exhibit a strong relationship between porosity and depth. Overpressure in non-shale formations has to be estimated using a different method to avoid errors while predicting the pore pressure. In this study, a different method for pore pressure prediction has been performed by using the lateral transfer approach. Many offset wells were used to predict the pore pressure. Lateral transfer in the sand body was identified as the mechanism for overpressure. This form of overpressure cannot be identified by well logs, which makes the pore pressure prediction more complex. Building a 2D geomechanical model, using seismic data as an input and following an analysis methodology that considered three type of formation fluids - gas, oil and water in the sand body, all pore pressure gradients related to lateral transfer for the respective fluids were evaluated. This methodology was applied to a conventional reservoir in a field in Colombia and was helpful to select the appropriate mud weight and circulating pressure to mitigate drilling risks associated to this mechanism of overpressure. Seismic data was critical to identifying this type of overpressure mechanism and was one of the main inputs for building the geomechanical earth model. This methodology enables drilling engineers and geoscientists to confidently predict, assess and mitigate the risks posed by overpressure in non-shale formations where lateral transfer is the driving mechanism of overpressure. This will ensure a robust well plan and minimize drilling/well control hazards associated with this mode of overpressure.

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