Incorporating Seismic Data of Intermediate Vertical Resolution Into Three-Dimensional Reservoir Models: A New Method

1999 ◽  
Vol 2 (04) ◽  
pp. 325-333 ◽  
Author(s):  
R.A. Behrens ◽  
T.T. Tran

Summary Three-dimensional (3D) earth models are best created with a combination of well logs and seismic data. Seismic data have good lateral resolution but poor vertical resolution compared to wells. The seismic resolution depends on seismic acquisition and reservoir parameters, and is incorporated into the 3D earth model with different techniques depending on this resolution relative to that of the 3D model. Good vertical resolution of the seismic data may warrant integrating it as a continuous vertical variable informing local reservoir properties, whereas poor resolution warrants using only a single map representing vertically averaged reservoir properties. The first case best applies to thick reservoirs and/or high-frequency seismic data in soft rock and is usually handled using a cokriging-type approach. The second case represents the low end of the seismic resolution spectrum, where the seismic map can now be treated by methods such as block kriging, simulated annealing, or Bayesian techniques. We introduce a new multiple map Bayesian technique with variable weights for the important middle ground where a single seismic map cannot effectively represent the entire reservoir. This new technique extends a previous Bayesian technique by incorporating multiple seismic property maps and also allowing vertically varying weighting functions for each map. This vertical weighting flexibility is physically important because the seismic maps represent reflected wave averages from rock property contrasts such as at the top and base of the reservoir. Depending on the seismic acquisition and reservoir properties, the seismic maps are physically represented by simple but nonconstant weights in the new 3D earth modeling technique. Two field examples are shown where two seismic maps are incorporated in each 3D earth model. The benefit of using multiple maps is illustrated with the geostatistical concept of probability of exceedance. Finally, a postmortem is presented showing well path trajectories of a successful and unsuccessful horizontal well that are explained by model results based on data existing before the wells were drilled. Introduction Three-dimensional (3D) earth models are greatly improved by including seismic data because of the good lateral coverage compared with well data alone. The vertical resolution of seismic data is poor compared with well data, but it may be high or low compared with the reservoir thickness as depicted in Fig. 1. Seismic resolution is typically considered to be one-fourth of a wavelength (?/4) although zones of thinner rock property contrasts can be detected. The seismic resolution relative to the reservoir thickness constrains the applicability of different geostatistical techniques for building the 3D earth model. Fig. 1 is highly schematic and not meant to portray seismic data as a monochromatic (single-frequency) wave. The reference to wavelength here is based on the dominant frequency in the seismic data. Fig. 1 is meant to illustrate the various regimes of vertical resolution in seismic data relative to the reservoir thickness. While there are all sorts of issues, such as tuning, that must be considered in the left two cases, we need to address these cases because of their importance. Seismic data having little vertical resolution over the reservoir interval, as in the left case of Fig. 1 can use geostatistical techniques that incorporate one seismic attribute map. The single attribute can be a static combination of multiple attributes in a multivariate sense but the combination cannot vary spatially. These techniques include sequential Gaussian simulation with Block Kriging1 (SGSBK), simulated annealing,2 or sequential Gaussian simulation with Bayesian updating.3,4 Some of these methods are extendable beyond a single seismic map with modification. Seismic data having good vertical resolution over the reservoir interval, as in the right seismic trace of Fig. 1, can use geostatistical techniques that incorporate 3D volumes of seismic attributes. Techniques include simulated annealing, collocated cokriging simulation,5 a Markov-Bayes approach,6 and spectral separation. The term "3D volume" of seismic, as used here, is distinguished from the term "3D seismic data." (A geophysicist speaks of 3D seismic data when it is acquired over the surface in areal swaths or patches for the purpose of imaging a 3D volume of the earth. Two-dimensional (2D) seismic is acquired along a line on the surface for the purpose of imaging a 2D cross section of the earth.) The 3D volume distinction is made based on the vertical resolution of the seismic relative to the reservoir. To be considered a 3D volume here, we require both lateral and vertical resolution within the reservoir. Seismic data often do not have the vertical resolution within the reservoir zone to warrant using a 3D volume of seismic data. The low and high limits of vertical resolution leave out the case of intermediate vertical resolution as depicted by the middle curve of Fig. 1. Because typical seismic resolution often ranges from 10 to 40 m and many reservoirs have thicknesses one to two times this range, many reservoirs fall into this middle ground. These reservoirs have higher vertical seismic resolution than a single map captures, but not enough to warrant using a 3D volume of seismic. It is this important middle ground that is addressed by a new technique presented in this paper.

2017 ◽  
Vol 5 (3) ◽  
pp. SJ21-SJ30 ◽  
Author(s):  
Ryan Michael Williams ◽  
Enric Pascual-Cebrian ◽  
Jon Charles Gutmanis ◽  
Gaynor Suzanne Paton

The “seismic resolution gap” has been an area of ambiguity ever since the results of 3D seismic interpretation have been used as inputs for modeling purposes because many important structural events such as fractures are at or below seismic resolution, which can impinge reservoir properties such as porosity and permeability. Having the means to accurately map these events with confidence has always been a challenge. More often than not, localized mapping of these features at borehole conditions can be achieved by core or image-log analysis. Seismic-derived attributes have assisted in improving the interwell geologic understanding in a lateral sense, but they are always hampered by vertical resolution. Enhanced imaging, such as cyan-magenta-yellow blending of attributes, has helped improve the lateral understanding of fracture patterns and networks, as shown in this workflow, but the challenge with vertical resolution still persists. However, by combining borehole and seismic data studies in a distinct workflow, it has become possible to identify overlaps and misalignments, which in turn has assisted in identification of discrete structural patterns not previously identified because of the seismic resolution gap. These results will then be used to improve the confidence of structural interpretation and static fracture models, which all go toward improving reservoir simulation models and geologic understanding.


1999 ◽  
Vol 2 (04) ◽  
pp. 334-340 ◽  
Author(s):  
Philippe Lamy ◽  
P.A. Swaby ◽  
P.S. Rowbotham ◽  
Olivier Dubrule ◽  
A. Haas

Summary The methodology presented in this paper incorporates seismic data, geological knowledge and well logs to produce models of reservoir parameters and uncertainties associated with them. A three-dimensional (3D) seismic dataset is inverted within a geological and stratigraphic model using the geostatistical inversion technique. Several reservoir-scale acoustic impedance blocks are obtained and quantification of uncertainty is determined by computing statistics on these 3D blocks. Combining these statistics with the kriging of the reservoir parameter well logs allows the transformation of impedances into reservoir parameters. This combination is similar to performing a collocated cokriging of the acoustic impedances. Introduction Our geostatistical inversion approach is used to invert seismic traces within a geological and stratigraphic model. At each seismic trace location, a large number of acoustic impedance (AI) traces are generated by conditional simulation, and a local objective function is minimized to find the trace that best fits the actual seismic trace. Several three-dimensional (3D) AI realizations are obtained, all of which are constrained by both the well logs and seismic data. Statistics are then computed in each stratigraphic cell of the 3D results to quantify the nonuniqueness of the solution and to summarize the information provided by individual realizations. Finally, AI are transformed into other reservoir parameters such as Vshale through a statistical petrophysical relationship. This transformation is used to map Vshale between wells, by combining information derived from Vshale logs with information derived from AI blocks. The final block(s) can then be mapped from the time to the depth domain and used for building the flow simulation models or for defining reservoir characterization maps (e.g., net to gross, hydrocarbon pore volume). We illustrate the geostatistical inversion method with results from an actual case study. The construction of the a-priori model in time, the inversion, and the final reservoir parameters in depth are described. These results show the benefit of a multidisciplinary approach, and illustrate how the geostatistical inversion method provides clear quantification of uncertainties affecting the modeling of reservoir properties between wells. Methodology The Geostatistical Inversion Approach. This methodology was introduced by Bortoli et al.1 and Haas and Dubrule.2 It is also discussed in Dubrule et al.3 and Rowbotham et al.4 Its application on a synthetic case is described in Dubrule et al.5 A brief review of the method will be presented here, emphasizing how seismic data and well logs are incorporated into the inversion process. The first step is to build a geological model of the reservoir in seismic time. Surfaces are derived from sets of picks defining the interpreted seismic. These surfaces are important sincethey delineate the main layers of the reservoir and, as we will see below, the statistical model associated with these layers, andthey control the 3D stratigraphic grid construction. The structure of this grid (onlap, eroded, or proportional) depends on the geological context. The maximum vertical discretization may be higher than that of the seismic, typically from 1 to 4 milliseconds. The horizontal discretization is equal to the number of seismic traces to invert in each direction (one trace per cell in map view). Raw AI logs at the wells have to be located within this stratigraphic grid since they will be used as conditioning data during the inversion process. It is essential that well logs should be properly calibrated with the seismic. This implies that a representative seismic wavelet has been matched to the wells, by comparing the convolved reflectivity well log response with the seismic response at the same location. This issue is described more fully in Rowbotham et al.4 Geostatistical parameters are determined by using both the wells and seismic data. Lateral variograms are computed from the seismic mapped into the stratigraphic grid. Well logs are used to both give an a priori model (AI mean and standard deviation) per stratum and to compute vertical variograms. The geostatistical inversion process can then be started. A random path is followed by the simulation procedure, and at each randomly drawn trace location AI trace values can be generated by sequential Gaussian simulation (SGS). A large number of AI traces are generated at the same location and the corresponding reflectivities are calculated. After convolution with the wavelet, the AI trace that leads to the best fit with the actual seismic is kept and merged with the wells and the previously simulated AI traces. The 3D block is therefore filled sequentially, trace after trace (see Fig. 1). It is possible to ignore the seismic data in the simulation process by generating only one trace at any (X, Y) location and automatically keeping it as "the best one." In this case, realizations are only constrained by the wells and the geostatistical model (a-priori parameters and variograms).


2021 ◽  
Vol 40 (7) ◽  
pp. 484-493
Author(s):  
Doha Monier ◽  
Azza El Rawy ◽  
Abdullah Mahmoud

The Nile Delta Basin is a major gas province. Commercial gas discoveries there have been proven mainly in Pleistocene to Oligocene sediments, and most discoveries are within sandstone reservoirs. Three-dimensional seismic data acquired over the basin have helped greatly in imaging and visualization of stratigraphy and structure, leading to robust understanding of the subsurface. Channel fairways serve as potential reservoir units; hence, mapping channel surfaces and identifying and defining infill lithology is important. Predicting sand distribution and reservoir presence is one of the key tasks as well as one of the key uncertainties in exploration. Integrating state-of-the-art technologies, such as including 3D seismic reflection surveys, seismic attributes, and geobody extractions, can reduce this uncertainty through recognition and accurate mapping of channel features. In this study, seismic attribute analysis, frequency analysis through spectral decomposition (SD), geobodies, and seismic sections have been used to delineate shallow Plio-Pleistocene El Wastani Formation channel fairways within the Saffron Field, offshore Nile Delta, Egypt. This has led to providing more reliable inputs for calculation of volumetrics. Interpretation of the stacked-channels complex through different seismic attributes helped to discriminate between sand-filled and shale-filled channels and in understanding their geometries. Results include more confident delineation of four distinct low-sinuosity channelized features. Petrophysical evaluation conducted on five wells penetrating Saffron reservoirs included electric logs and modular dynamic test data interpretation. The calculated average reservoir properties were used in different volumetric calculation cases. Different approaches were applied to delineate channel geometries that were later used in performing different volumetric cases. These approaches included defining channels from root-mean-square amplitude extractions, SD color-blended frequencies, and geobodies, all calculated from prestack seismic data. The different volumetric cases performed were compared against the latest field volume estimates proven after several years of production in which an area-versus-depth input showed the closest calculated hydrocarbon volumes to the actual proven field volumes.


Geophysics ◽  
1985 ◽  
Vol 50 (12) ◽  
pp. 2411-2430 ◽  
Author(s):  
P. S. Horvath

Gulf began investigating three‐dimensional seismic surveys in the mid‐1960s through Gulf Research and Development Company. During the late 1960s, models were constructed to simulate acquisition and processing. Three‐dimensional (3-D) migration was achieved in the early 1970s, and Gulf began field testing 3-D seismic data acquisition in 1974. By 1978, 3-D seismic surveys were available as a commercial service through contractors. Some advantages that 3-D seismic surveys have over 2-D seismic surveys are: they can help refine both structure and stratigraphic interpretations; they assist in defining the paleogeology and reveal details otherwise not apparent; they help determine the reservoir limits through improved interpretation of the structure and hydrocarbon indicators; they enable the acquisition of subsurface control under surface obstructions, such as platforms, rigs, etc.; they provide the opportunity to construct profiles in any direction desired; and they lend themselves to interactive interpretation. When using 3-D seismic surveys, improved seismic resolution is expected. This in turn improves drilling success and finding new reserves, makes the development drilling program more efficient, and provides the best possible location for a wildcat survey. The results achieved in 16 3-D seismic surveys that cover 26 blocks in the offshore Gulf of Mexico reveal that offshore 3-D seismic surveys can be a cost‐effective way of finding and developing hydrocarbons.


Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. R429-R448 ◽  
Author(s):  
Maryam Hadavand Siri ◽  
Clayton V. Deutsch

We have developed a fully coupled categorical-multivariate continuous stochastic inversion with a combined petro-elastic model and convolution. The new multivariate stochastic seismic inversion approach simulates multiple reservoir properties simultaneously and conditions them to the well and seismic data at the same time through the close integration of multivariate geostatistical modeling and stochastic inversion. This approach combines a trace-by-trace (column-wise) adaptive sampling algorithm with multivariate geostatistical techniques to select reservoir properties that match the seismic data. The adaptive sampling method uses an acceptance-rejection approach to condition geostatistical models to the well and seismic data. The adaptive sampling algorithm defines a practical stopping criteria based on the inherent uncertainty due to modeling assumptions and the size of the uncertainty space. This technique samples the realizations inside the space of uncertainty; the number of realizations attempted increases with the size of the space of uncertainty. Characterizing multiple reservoir properties simultaneously through the close integration of seismic inversion and multivariate geostatistical techniques leads to improved high-resolution reservoir property models that reproduce the original seismic data. A case study is considered to compare the proposed stochastic inversion approach with the conventional methods. The case study represents multivariate stochastic inversion provides high-resolution facies and reservoir physical properties simultaneously that reproduce the original seismic data within quality of data better than the other approaches.


Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. O9-O17 ◽  
Author(s):  
Upendra K. Tiwari ◽  
George A. McMechan

In inversion of viscoelastic full-wavefield seismic data, the choice of model parameterization influences the uncertainties and biases in estimating seismic and petrophysical parameters. Using an incomplete model parameterization results in solutions in which the effects of missing parameters are attributed erroneously to the parameters that are included. Incompleteness in this context means assuming the earth is elastic rather than viscoelastic. The inclusion of compressional and shear-wave quality factors [Formula: see text] and [Formula: see text] in inversion gives better estimates of reservoir properties than the less complete (elastic) model parameterization. [Formula: see text] and [Formula: see text] are sensitive primarily to fluid types and saturations. The parameter correlations are sensitive also to the model parameterization. As noise increases in the viscoelastic input data, the resolution of the estimated parameters decreases, but the parameter correlations are relatively unaffected by modest noise levels.


2021 ◽  
Vol 45 (3) ◽  
Author(s):  
C. M. Durnea ◽  
S. Siddiqi ◽  
D. Nazarian ◽  
G. Munneke ◽  
P. M. Sedgwick ◽  
...  

AbstractThe feasibility of rendering three dimensional (3D) pelvic models of vaginal, urethral and paraurethral lesions from 2D MRI has been demonstrated previously. To quantitatively compare 3D models using two different image processing applications: 3D Slicer and OsiriX. Secondary analysis and processing of five MRI scan based image sets from female patients aged 29–43 years old with vaginal or paraurethral lesions. Cross sectional image sets were used to create 3D models of the pelvic structures with 3D Slicer and OsiriX image processing applications. The linear dimensions of the models created using the two different methods were compared using Bland-Altman plots. The comparisons demonstrated good agreement between measurements from the two applications. The two data sets obtained from different image processing methods demonstrated good agreement. Both 3D Slicer and OsiriX can be used interchangeably and produce almost similar results. The clinical role of this investigation modality remains to be further evaluated.


2005 ◽  
Vol 127 (3) ◽  
pp. 336-344 ◽  
Author(s):  
Shyamal C. Mondal ◽  
Paul D. Wilcox ◽  
Bruce W. Drinkwater

Two-dimensional (2D) phased arrays have the potential to significantly change the way in which engineering components in safety critical industries are inspected. In addition to enabling a three-dimensional (3D) volume of a component to be inspected from a single location, they could also be used in a C-scan configuration. The latter would enable any point in a component to be interrogated over a range of solid angles, allowing more accurate defect characterization and sizing. This paper describes the simulation and evaluation of grid, cross and circular 2D phased array element configurations. The aim of the cross and circle configurations is to increase the effective aperture for a given number of elements. Due to the multitude of possible array element configurations a model, based on Huygens’ principle, has been developed to allow analysis and comparison of candidate array designs. In addition to the element configuration, key issues such as element size, spacing, and frequency are discussed and quantitatively compared using the volume of the 3D point spread function (PSF) as a measurand. The results of this modeling indicate that, for a given number of elements, a circular array performs best and that the element spacing should be less than half a wavelength to avoid grating lobes. A prototype circular array has been built and initial results are presented. These show that a flat bottomed hole, half a wavelength in diameter, can be imaged. Furthermore, it is shown that the volume of the 3D reflection obtained experimentally from the end of the hole compares well with the volume of the 3D PSF predicted for the array at that point.


Geophysics ◽  
1988 ◽  
Vol 53 (7) ◽  
pp. 894-902 ◽  
Author(s):  
Ruhi Saatçilar ◽  
Nezihi Canitez

Amplitude‐ and frequency‐modulated wave motion constitute the ground‐roll noise in seismic reflection prospecting. Hence, it is possible to eliminate ground roll by applying one‐dimensional, linear frequency‐modulated matched filters. These filters effectively attenuate the ground‐roll energy without damaging the signal wavelet inside or outside the ground roll’s frequency interval. When the frequency bands of seismic reflections and ground roll overlap, the new filters eliminate the ground roll more effectively than conventional frequency and multichannel filters without affecting the vertical resolution of the seismic data.


Sign in / Sign up

Export Citation Format

Share Document