Predicting reservoir quality in the Bakken Formation, North Dakota, using petrophysics and 3C seismic data

2020 ◽  
Vol 8 (4) ◽  
pp. T851-T868
Author(s):  
Andrea G. Paris ◽  
Robert R. Stewart
Keyword(s):  
North Dakota ◽  
Seismic Data ◽  
Rock Physics ◽  
P Wave ◽  
Well Logs ◽  
Reservoir Quality ◽  
Bakken Formation ◽  
S Wave ◽  
Converted Wave ◽  
Wave Velocities

Combining rock-property analysis with multicomponent seismic imaging can be an effective approach for reservoir quality prediction in the Bakken Formation, North Dakota. The hydrocarbon potential of shale is indicated on well logs by low density, high gamma-ray response, low compressional-wave (P-wave) and shear-wave (S-wave) velocities, and high neutron porosity. We have recognized the shale intervals by cross plotting sonic velocities versus density. Intervals with total organic carbon (TOC) content higher than 10 wt% deviate from lower TOC regions in the density domain and exhibit slightly lower velocities and densities (<2.30 g/cm3). We consider TOC to be the principal factor affecting changes in the density and P- and S-wave velocities in the Bakken shales, where VP/ VS ranges between 1.65 and 1.75. We generate the synthetic seismic data using an anisotropic version of the Zoeppritz equations, including estimated Thomsen’s parameters. For the tops of the Upper and Lower Bakken, the amplitude shows a negative intercept and a positive gradient, which corresponds to an amplitude variation with offset of class IV. The P-impedance error decreases by 14% when incorporating the converted-wave information in the inversion process. A statistical approach using multiattribute analysis and neural networks delimits the zones of interest in terms of P-impedance, density, TOC content, and brittleness. The inverted and predicted results show reasonable correlations with the original well logs. The integration of well log analysis, rock physics, seismic modeling, constrained inversions, and statistical predictions contributes to identifying the areas of highest reservoir quality within the Bakken Formation.

Estimating shear‐wave velocities from P-wave and converted‐wave data

Geophysics ◽  
1999 ◽  
Vol 64 (2) ◽  
pp. 504-507 ◽  
Author(s):  
Franklyn K. Levin
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
Wave Data ◽  
Wave Velocities ◽  
Shear Wave Velocities ◽  
P Wave Velocity ◽  
Growing Body

Tessmer and Behle (1988) show that S-wave velocity can be estimated from surface seismic data if both normal P-wave data and converted‐wave data (P-SV) are available. The relation of Tessmer and Behle is [Formula: see text] (1) where [Formula: see text] is the S-wave velocity, [Formula: see text] is the P-wave velocity, and [Formula: see text] is the converted‐wave velocity. The growing body of converted‐wave data suggest a brief examination of the validity of equation (1) for velocities that vary with depth.

Elastic reflectivity vectors and the geometry of intercept-gradient crossplots

2019 ◽  
Vol 38 (10) ◽  
pp. 762-769
Author(s):  
Patrick Connolly
Keyword(s):  
Elastic Property ◽  
Elastic Properties ◽  
Wave Velocity ◽  
Seismic Data ◽  
Measurement Errors ◽  
Rock Physics ◽  
P Wave ◽  
S Wave ◽  
P Wave Velocity ◽  
Well Log Analysis

Reflectivities of elastic properties can be expressed as a sum of the reflectivities of P-wave velocity, S-wave velocity, and density, as can the amplitude-variation-with-offset (AVO) parameters, intercept, gradient, and curvature. This common format allows elastic property reflectivities to be expressed as a sum of AVO parameters. Most AVO studies are conducted using a two-term approximation, so it is helpful to reduce the three-term expressions for elastic reflectivities to two by assuming a relationship between P-wave velocity and density. Reduced to two AVO components, elastic property reflectivities can be represented as vectors on intercept-gradient crossplots. Normalizing the lengths of the vectors allows them to serve as basis vectors such that the position of any point in intercept-gradient space can be inferred directly from changes in elastic properties. This provides a direct link between properties commonly used in rock physics and attributes that can be measured from seismic data. The theory is best exploited by constructing new seismic data sets from combinations of intercept and gradient data at various projection angles. Elastic property reflectivity theory can be transferred to the impedance domain to aid in the analysis of well data to help inform the choice of projection angles. Because of the effects of gradient measurement errors, seismic projection angles are unlikely to be the same as theoretical angles or angles derived from well-log analysis, so seismic data will need to be scanned through a range of angles to find the optimum.

A rock-physics model to determine the pore microstructure of cracked porous rocks

2020 ◽  
Vol 223 (1) ◽  
pp. 622-631
Author(s):  
Lin Zhang ◽  
Jing Ba ◽  
José M Carcione
Keyword(s):  
Crack Density ◽  
Rock Physics ◽  
Differential Pressure ◽  
P Wave ◽  
Porous Rocks ◽  
S Wave ◽  
Wave Velocities ◽  
Pore Microstructure ◽  
Physics Model ◽  
Rock Physics Model

SUMMARY Determining rock microstructure remains challenging, since a proper rock-physics model is needed to establish the relation between pore microstructure and elastic and transport properties. We present a model to estimate pore microstructure based on porosity, ultrasonic velocities and permeability, assuming that the microstructure consists on randomly oriented stiff equant pores and penny-shaped cracks. The stiff pore and crack porosity varying with differential pressure is estimated from the measured total porosity on the basis of a dual porosity model. The aspect ratio of pores and cracks and the crack density as a function of differential pressure are obtained from dry-rock P- and S-wave velocities, by using a differential effective medium model. These results are used to invert the pore radius from the matrix permeability by using a circular pore model. Above a crack density of 0.13, the crack radius can be estimated from permeability, and below that threshold, the radius is estimated from P-wave velocities, taking into account the wave dispersion induced by local fluid flow between pores and cracks. The approach is applied to experimental data for dry and saturated Fontainebleau sandstone and Chelmsford Granite.

Converted-wave model building and imaging based on common-focus-point methodology

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. U139-U149
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali ◽  
Yi Luo
Keyword(s):  
Elastic Wave ◽  
Wave Velocity ◽  
Seismic Data ◽  
Model Building ◽  
P Wave ◽  
Rock Properties ◽  
S Wave ◽  
Converted Wave ◽  
Seismic Images ◽  
Focus Point

Seismic images can be viewed as photographs for underground rocks. These images can be generated from different reflections of elastic waves with different rock properties. Although the dominant seismic data processing is still based on the acoustic wave assumption, elastic wave processing and imaging have become increasingly popular in recent years. A major challenge in elastic wave processing is shear-wave (S-wave) velocity model building. For this reason, we have developed a sequence of procedures for estimating seismic S-wave velocities and the subsequent generation of seismic images using converted waves. We have two main essential new supporting techniques. The first technique is the decoupling of the S-wave information by generating common-focus-point gathers via application of the compressional-wave (P-wave) velocity on the converted seismic data. The second technique is to assume one common VP/ VS ratio to approximate two types of ratios, namely, the ratio of the average earth layer velocity and the ratio of the stacking velocity. The benefit is that we reduce two unknown ratios into one, so it can be easily scanned and picked in practice. The PS-wave images produced by this technology could be aligned with the PP-wave images such that both can be produced in the same coordinate system. The registration between the PP and PS images provides cross-validation of the migrated structures and a better estimation of underground rock and fluid properties. The S-wave velocity, computed from the picked optimal ratio, can be used not only for generating the PS-wave images, but also to ensure well registration between the converted-wave and P-wave images.

Petroacoustics and composition of presalt rocks from Santos Basin

2019 ◽  
Vol 38 (5) ◽  
pp. 342-348 ◽  
Author(s):  
Guilherme Fernandes Vasquez ◽  
Marcio José Morschbacher ◽  
Camila Wense Dias dos Anjos ◽  
Yaro Moisés Parisek Silva ◽  
Vanessa Madrucci ◽  
...  
Keyword(s):  
Clay Minerals ◽  
Chemical Elements ◽  
Pore Space ◽  
Rock Physics ◽  
P Wave ◽  
Rock Properties ◽  
Tectonic Activity ◽  
S Wave ◽  
Wave Velocities ◽  
Lacustrine Carbonate

The deposition of the presalt section from Santos Basin began when Gondwana started to break up and South America and Africa were separating. Initial synrift carbonate deposits affected by relatively severe tectonic activity evolved to a lacustrine carbonate environment during the later stages of basin formation. Although the reservoirs are composed of carbonate rocks, the occurrence of faults and the intense colocation of igneous rocks served as a source of chemical elements uncommon in typical carbonate environments. Consequently, beyond the presence of different facies with complex textures and pore geometries, the presalt reservoir rocks present marked compositional and microstructural variability. Therefore, rock-physics modeling is used to understand and interpret the extensive laboratory measurements of P-wave velocities, S-wave velocities, and density that we have undertaken on the presalt carbonate cores from Santos Basin. We show that quartz and exotic clay minerals (such as stevensite and other magnesium-rich clay minerals), which have different values of elastic moduli and Poisson's ratio as compared to calcite and dolomite, may introduce noticeable “Poisson's reflectivity anomalies” on prestack seismic data. Moreover, although the authors concentrate their attention on composition, it will become clear that pore-space geometry also may influence seismic rock properties of presalt carbonate reservoirs.

Sediments with gas hydrates: Internal structure from seismic AVO

Geophysics ◽  
1998 ◽  
Vol 63 (5) ◽  
pp. 1659-1669 ◽  
Author(s):  
Christine Ecker ◽  
Jack Dvorkin ◽  
Amos Nur
Keyword(s):  
Internal Structure ◽  
Wave Velocity ◽  
Seismic Data ◽  
Pore Space ◽  
Rock Physics ◽  
P Wave ◽  
S Wave ◽  
High Concentration ◽  
Amplitude Variation With Offset ◽  
Bottom Simulating Reflector

We interpret amplitude variation with offset (AVO) data from a bottom simulating reflector (BSR) offshore Florida by using rock‐physics‐based synthetic seismic models. A previously conducted velocity and AVO analysis of the in‐situ seismic data showed that the BSR separates hydrate‐bearing sediments from sediments containing free methane. The amplitude at the BSR are increasingly negative with increasing offset. This behavior was explained by P-wave velocity above the BSR being larger than that below the BSR, and S-wave velocity above the BSR being smaller than that below the BSR. We use these AVO and velocity results to infer the internal structure of the hydrated sediment. To do so, we examine two micromechanical models that correspond to the two extreme cases of hydrate deposition in the pore space: (1) the hydrate cements grain contacts and strongly reinforces the sediment, and (2) the hydrate is located away from grain contacts and does not affect the stiffness of the sediment frame. Only the second model can qualitatively reproduce the observed AVO response. Thus inferred internal structure of the hydrate‐bearing sediment means that (1) the sediment above the BSR is uncemented and, thereby, mechanically weak, and (2) its permeability is very low because the hydrate clogs large pore‐space conduits. The latter explains why free gas is trapped underneath the BSR. The seismic data also indicate the absence of strong reflections at the top of the hydrate layer. This fact suggests that the high concentration of hydrates in the sediment just above the BSR gradually decreases with decreasing depth. This effect is consistent with the fact that the low‐permeability hydrated sediments above the BSR prevent free methane from migrating upwards.

scholarly journals Identification of hydrocarbons in chalk reservoirs from surface seismic data: South Arne field, North Sea

2005 ◽  
Vol 7 ◽  
pp. 13-16
Author(s):  
Peter Japsen ◽  
Anders Bruun ◽  
Ida L. Fabricius ◽  
Gary Mavko
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Seismic Data ◽  
Pore Space ◽  
Sedimentary Rocks ◽  
Rock Physics ◽  
Acoustic Properties ◽  
P Wave ◽  
S Wave ◽  
Reservoir Rocks

Seismic data are mainly used to map out structures in the subsurface, but are also increasingly used to detect differences in porosity and in the fluids that occupy the pore space in sedimentary rocks. Hydrocarbons are generally lighter than brine, and the bulk density and sonic velocity (speed of pressure waves or P-wave velocity) of hydrocarbon-bearing sedimentary rocks are therefore reduced compared to non-reservoir rocks. However, sound is transmitted in different wave forms through the rock, and the shear velocity (speed of shear waves or S-wave velocity) is hardly affected by the density of the pore fluid. In order to detect the presence of hydrocarbons from seismic data, it is thus necessary to investigate how porosity and pore fluids affect the acoustic properties of a sedimentary rock. Much previous research has focused on describing such effects in sandstone (see Mavko et al. 1998), and only in recent years have corresponding studies on the rock physics of chalk appeared (e.g. Walls et al. 1998; Røgen 2002; Fabricius 2003; Gommesen 2003; Japsen et al. 2004). In the North Sea, chalk of the Danian Ekofisk Formation and the Maastrichtian Tor Formation are important reservoir rocks. More information could no doubt be extracted from seismic data if the fundamental physical properties of chalk were better understood. The presence of gas in chalk is known to cause a phase reversal in the seismic signal (Megson 1992), but the presence of oil in chalk has only recently been demonstrated to have an effect on surface seismic data (Japsen et al. 2004). The need for a better link between chalk reservoir parameters and geophysical observations has, however, strongly increased since the discovery of the Halfdan field proved major reserves outside four-way dip closures (Jacobsen et al. 1999; Vejbæk & Kristensen 2000).

Time-average equation revisited

Geophysics ◽  
1998 ◽  
Vol 63 (2) ◽  
pp. 460-464 ◽  
Author(s):  
Jack Dvorkin ◽  
Amos Nur
Keyword(s):  
Solid Phase ◽  
Rock Physics ◽  
Pore Fluid ◽  
P Wave ◽  
Well Logs ◽  
Fluid Type ◽  
Wave Velocities ◽  
P Wave Velocity ◽  
Solid Phase Material

Expressions that relate velocity to porosity and to pore-fluid compressibility are among the most important deliverables of rock physics. Such relations are used often as additional controls for inferring porosity from well logs, as well as in-situ indicators of pore fluid type. The oldest and most popular is the Wyllie et al. (1956) equation: [Formula: see text]where [Formula: see text] is the measured traveltime of a P-wave, [Formula: see text] is the traveltime expected in the solid-phase material, and [Formula: see text] is the traveltime expected in the pore fluid. It follows from equation (1) that [Formula: see text]where ϕ is porosity, [Formula: see text] is the measured P-wave velocity, and [Formula: see text] and [Formula: see text] are the P-wave velocities in the solid and in the pore-fluid phases, respectively.

An Adaptive Stratified Joint PP and PS AVA Inversion Using Accurate Jacobian Matrix

Geophysics ◽  
2021 ◽  
pp. 1-145
Author(s):  
Xiaobo Liu ◽  
Jingyi Chen ◽  
Jing Zeng ◽  
Fuping Liu ◽  
Handong Huang ◽  
...  
Keyword(s):  
Seismic Data ◽  
Jacobian Matrix ◽  
Incidence Angle ◽  
P Wave ◽  
Rock Properties ◽  
Inversion Method ◽  
S Wave ◽  
Zoeppritz Equations ◽  
Wave Velocities ◽  
Strong Contrast

Amplitude variation with incidence angle (AVA) analysis is an essential tool for discriminating lithology in the hydrocarbon reservoirs. Compared with the traditional AVA inversion using only P-wave information, joint AVA inversion using PP and PS seismic data provides better estimation of rock properties (e.g., density, P- and S-wave velocities). At present, the most used AVA inversions depend on the approximations of Zoeppritz equations (e.g., Shuey and Aki-Richards approximations), which are not suitable for formations with strong contrast interfaces and seismic data with large incidence angles. Based on the previous derivation of accurate Jacobian matrix, we find that the sign of each partial derivative of reflection coefficient with respect to P-, S-wave velocities and density changes across the interface, represents good indicator for the reflection interfaces. Accordingly, we propose an adaptive stratified joint PP and PS AVA inversion using the accurate Jacobian matrix that can automatically obtain the layer information and can be further used as a constraint in the inversion of in-layer rock properties (density, P- and S-wave velocities). Due to the use of the exact Zoeppritz equations and accurate Jacobian matrix, this proposed inversion method is more accurate than traditional AVA inversion methods, has higher computational efficiency and can be applied to seismic wide-angle reflection data or seismic data acquired for formations with strong contrast interfaces. The model study shows that this proposed inversion method works better than the classical Shuey and Aki-Richards approximations at estimating reflection interfaces and in-layer rock properties. It also works well in handling a part of the complex Marmousi 2 model and real seismic data.

Elastic FWI for orthorhombic media with lithologic constraints applied via machine learning

Geophysics ◽  
2021 ◽  
pp. 1-86
Author(s):  
Sagar Singh ◽  
Ilya Tsvankin ◽  
Ehsan Zabihi Naeini
Keyword(s):  
Machine Learning ◽  
Model Updating ◽  
Waveform Inversion ◽  
Rock Physics ◽  
P Wave ◽  
Supervised Machine Learning ◽  
Well Logs ◽  
Support Vector ◽  
S Wave ◽  
Trade Offs

Full-waveform inversion (FWI) of 3D wide-azimuth data for elastic orthorhombic media suffers from parameter trade-offs which cannot be overcome without constraining the model-updating procedure. We present an FWI methodology that incorporates geologic constraints to reduce the inversion nonlinearity and increase the resolution of parameter estimation for orthorhombic models. These constraints are obtained from well logs, which can provide rock-physics relationships for different geologic facies. Because the locations of the available well logs are usually sparse, a supervised machine-learning (ML) algorithm (Support Vector Machine) is employed to account for lateral heterogeneity in building the lithologic constraints. The advantages of the facies-based FWI are demonstrated on the modified SEG-EAGE 3D overthrust model, which is made orthorhombic with the symmetry planes that coincide with the Cartesian coordinate planes. We employ a velocity-based parameterization, whose suitability for FWI is studied using the radiation-pattern analysis in a companion paper. Application of the facies-based constraints substantially increases the resolution of the P- and S-wave vertical velocities ( VP0, VS0, and VS1) and, therefore, of the depth scale of the model. Improvements are also observed for the P-wave horizontal and normal-moveout velocities ( VP1, VP2, Vnmo,1, and Vnmo,2) and the S-wave horizontal velocity VS2. However, the velocity Vnmo,3 that depends on Tsvankin’s parameter δ(3) defined in the horizontal plane is not well recovered from the surface data. On the whole, the developed algorithm achieves a much higher spatial resolution compared to unconstrained FWI, even in the absence of recorded frequencies below 2 Hz.

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