Optimal dynamic rock-fluid physics template validated by petroelastic reservoir modeling

Geophysics ◽  
2011 ◽  
Vol 76 (6) ◽  
pp. O45-O58 ◽  
Author(s):  
Alireza Shahin ◽  
Robert Tatham ◽  
Paul Stoffa ◽  
Kyle Spikes

Separation of fluid pore pressure and saturation using inverted time-lapse seismic attributes is a mandatory task for field development. Multiple pairs of inversion-derived attributes can be used in a crossplot domain. We performed a sensitivity analysis to determine an optimal crossplot, and the validity of the separation is tested with a comprehensive petroelastic reservoir model. We simulated a poorly consolidated shaly sandstone reservoir based on a prograding near-shore depositional environment. A model of effective porosity is first simulated by Gaussian geostatistics. Well-known theoretical and experimental petrophysical correlations were then efficiently combined to consistently simulate reservoir properties. Next, the reservoir model was subjected to numerical simulation of multiphase fluid flow to predict the spatial distributions of fluid saturation and pressure. A geologically consistent rock physics model was then used to simulate the inverted seismic attributes. Finally, we conducted a sensitivity analysis of seismic attributes and their crossplots as a tool to discriminate the effect of pressure and saturation. The sensitivity analysis demonstrates that crossplotting of acoustic impedance versus shear impedance should be the most stable way to separate saturation and pressure changes compared to other crossplots (e.g., velocity ratio versus acoustic impedance). We also demonstrated that the saturation and pressure patterns were detected in most of the time-lapse scenarios; however, the saturation pattern is more likely detectable because the percentage in pressure change is often lower than that of the saturation change. Imperfections in saturation and pressure patterns exist in various forms, and they can be explained by the interaction of saturation and pressure, the diffusive nature of pressure, and rapid change in pressure due to production operations.

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. C81-C92 ◽  
Author(s):  
Helene Hafslund Veire ◽  
Hilde Grude Borgos ◽  
Martin Landrø

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.


1997 ◽  
Author(s):  
Miron B. Rapoport ◽  
Valery I. Ryjkov ◽  
Larisa I. Rapoport ◽  
Vladislav E. Parnikel ◽  
Valentin A. Kateli ◽  
...  

SPE Journal ◽  
2017 ◽  
Vol 22 (04) ◽  
pp. 1261-1279 ◽  
Author(s):  
Shingo Watanabe ◽  
Jichao Han ◽  
Gill Hetz ◽  
Akhil Datta-Gupta ◽  
Michael J. King ◽  
...  

Summary We present an efficient history-matching technique that simultaneously integrates 4D repeat seismic surveys with well-production data. This approach is particularly well-suited for the calibration of the reservoir properties of high-resolution geologic models because the seismic data are areally dense but sparse in time, whereas the production data are finely sampled in time but spatially averaged. The joint history matching is performed by use of streamline-based sensitivities derived from either finite-difference or streamline-based flow simulation. For the most part, earlier approaches have focused on the role of saturation changes, but the effects of pressure have largely been ignored. Here, we present a streamline-based semianalytic approach for computing model-parameter sensitivities, accounting for both pressure and saturation effects. The novelty of the method lies in the semianalytic sensitivity computations, making it computationally efficient for high-resolution geologic models. The approach is implemented by use of a finite-difference simulator incorporating the detailed physics. Its efficacy is demonstrated by use of both synthetic and field applications. For both the synthetic and the field cases, the advantages of incorporating the time-lapse variations are clear, seen through the improved estimation of the permeability distribution, the pressure profile, the evolution of the fluid saturation, and the swept volumes.


Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. M1-M14 ◽  
Author(s):  
Donald W. Vasco ◽  
Andrey Bakulin ◽  
Hyoungsu Baek ◽  
Lane R. Johnson

Time-lapse geophysical monitoring has potential as a tool for reservoir characterization, that is, for determining reservoir properties such as permeability. Onset times, the calendar times at which geophysical observations begin to deviate from their initial or background values, provide a useful basis for such characterization. We found that, in contrast to time-lapse amplitude changes, onset times were not sensitive to the exact method used to related changes in fluid saturation to changes in seismic velocities. As a consequence of this, we found that an inversion for effective permeability based upon onset times was robust with respect to variations in the rock-physics model. In particular, inversions of synthetic onset times calculated using Voigt and Reuss averaging techniques, but inverted using sensitivities from Hill’s averaging method, resulted in almost identical misfit reductions and similar permeability models. All solutions based on onset times recovered the large-scale, resolvable features of the reference model. Synthetic tests indicated that reliable onset times can be obtained from noisy seismic amplitudes. Testing also indicated that large-scale permeability variations can be recovered even if we used onset times from seismic surveys that were spaced as much as 300 days apart.


2021 ◽  
pp. 1-69
Author(s):  
Marwa Hussein ◽  
Robert R. Stewart ◽  
Deborah Sacrey ◽  
Jonny Wu ◽  
Rajas Athale

Net reservoir discrimination and rock type identification play vital roles in determining reservoir quality, distribution, and identification of stratigraphic baffles for optimizing drilling plans and economic petroleum recovery. Although it is challenging to discriminate small changes in reservoir properties or identify thin stratigraphic barriers below seismic resolution from conventional seismic amplitude data, we have found that seismic attributes aid in defining the reservoir architecture, properties, and stratigraphic baffles. However, analyzing numerous individual attributes is a time-consuming process and may have limitations for revealing small petrophysical changes within a reservoir. Using the Maui 3D seismic data acquired in offshore Taranaki Basin, New Zealand, we generate typical instantaneous and spectral decomposition seismic attributes that are sensitive to lithologic variations and changes in reservoir properties. Using the most common petrophysical and rock typing classification methods, the rock quality and heterogeneity of the C1 Sand reservoir are studied for four wells located within the 3D seismic volume. We find that integrating the geologic content of a combination of eight spectral instantaneous attribute volumes using an unsupervised machine-learning algorithm (self-organizing maps [SOMs]) results in a classification volume that can highlight reservoir distribution and identify stratigraphic baffles by correlating the SOM clusters with discrete net reservoir and flow-unit logs. We find that SOM classification of natural clusters of multiattribute samples in the attribute space is sensitive to subtle changes within the reservoir’s petrophysical properties. We find that SOM clusters appear to be more sensitive to porosity variations compared with lithologic changes within the reservoir. Thus, this method helps us to understand reservoir quality and heterogeneity in addition to illuminating thin reservoirs and stratigraphic baffles.


2012 ◽  
Vol 15 (05) ◽  
pp. 571-583 ◽  
Author(s):  
C.S.. S. Kabir ◽  
M.. Elgmati ◽  
Z.. Reza

Summary Estimating the average drainage-area pressure (pav) of individual wells is a cornerstone to any reservoir-management practice. Yet conventional methods do not always offer reliable solutions to this vexing problem. This study shows that transient flow-after-flow (FAF) testing offers an excellent opportunity to establish pav in a time-lapse mode, when conducted following operational shutdowns. Instrumented wells are natural candidates for FAF testing. Real-time surveillance offers the opportunity to perform rate-transient analysis that results in drainage volume and, consequently, pav. However, gathering quality rate data commensurate with pressure over a long producing period is fraught with uncertainty, which raises questions about the validity of the pav so obtained. In addition, continuous changes in drainage-boundary conditions pose modeling challenges with a given reservoir model. Therefore, the independent estimation of pav cannot be overemphasized. This paper presents a theroretical framework for transient FAF testing and also shows a pragmatic approach to handling pressure/rate data incoherence.


Author(s):  
A. Ogbamikhumi ◽  
T. Tralagba ◽  
E. E. Osagiede

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.


2021 ◽  
pp. 99-108
Author(s):  
Sergiy VYZHVA ◽  
Ihor SOLOVYOV ◽  
Ihor МYKHALEVYCH ◽  
Viktoriia KRUHLYK ◽  
Georgiy LISNY

Based on the results of numerous seismic studies carried out in the areas and fields of the Dnipro-Donets depression, the strategy to identify hydrocarbon traps in this region has been developed taking into account modern requirements for prospecting and exploration of gas and oil fields. The studies are designed to determine the favorable zones of hydrocarbon accumulations based on the analysis of the structural-tectonic model. A necessary element for solving such a problem is to aaply direct indicators of hydrocarbons to predict traps of the structural, lithological or combined type. It was determined that an effective approach to identify hydrocarbon traps in the region is attribute analysis employing seismic attributes such as seismic envelope, acoustic impedance or relative acoustic impedance. In most cases of practical importance, the analysis of the distribution of the values of these attributes turned out to be sufficient for performing the geological tasks. It is given an example of extracting additional useful information on the spatial distribution of hydrocarbon traps from volumetric images obtained from seismograms of common sources with a limited range of ray angles inclinations. To analyze the distributions of seismic attribute values, it is recommended to use the Geobody technology for detecting geological bodies as the most effective when using volumetric seismic data. The distributions of various properties of rocks, including zones of increased porosity or zones of presence of hydrocarbons are determined depending on the types of seismic attributes used in the analysis,. The use of several seismic attributes makes it possible to identify geological bodies saturated with hydrocarbons with increased porosity and the like. The paper provides examples of hydrocarbon traps recognition in the areas and fields of the Dnipro-Donets depression practically proved by wells. A generalization on the distribution of promising hydrocarbon areas on the Northern flank of the Dnipro-Donets depression and the relationship of this distribution with the identified structural elements of the geological subsoil is made. 


2017 ◽  
Vol 96 (5) ◽  
pp. s39-s46 ◽  
Author(s):  
Clemens A. Visser ◽  
Jose L. Solano Viota

AbstractThe assessment of the seismic hazard and risk associated with the extraction of gas from the Groningen field involves a chain of modelling efforts. The first step is a description of the 3D distribution of reservoir properties in the reservoir – the static reservoir model – and is the subject of this paper. Consecutive steps in the chain of models are described elsewhere in this volume. The construction of a static reservoir model is not strictly a scientific endeavour, but many of the applied modelling techniques are underpinned by extensive scientific research. This paper aims to give a general introduction to the approach followed by NAM to build static models for the Groningen field. More detailed accounts of the applied modelling techniques, the assessment of associated uncertainties or the usage of multiple modelling scenarios are beyond the scope of the current paper, but are referenced in the text.


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