Find the rocks and the fluids will follow — AVO as a tool for lithology classification

2014 ◽  
Vol 2 (2) ◽  
pp. SC77-SC91 ◽  
Author(s):  
Kester D. Waters ◽  
Michael A. C. Kemper
Keyword(s):  
Case Studies ◽  
Seismic Data ◽  
Oil And Gas ◽  
Rock Physics ◽  
Amplitude Variation With Offset ◽  
Primary Means ◽  
Interpretation Process ◽  
Close Cooperation ◽  
Key Steps

Full-stack seismic interpretation continues to be the primary means of subsurface interpretation. However, the underlying impact of amplitude variation with offset (AVO) is effectively ignored or overlooked during the full-stack interpretation process. Recent advances in well-logging and rock physics techniques highlight the fact that AVO is a useful tool not only for detection of fluid anomalies, but also for the detection and characterization of lithology. We evaluated an overview of some of the key steps in the rock physics assessment of well logs and seismic data, and highlight the potential to move toward a new convention of interpretation on so-called lithology stacks. Lithology stacks may come in a variety of forms but should form the focus of interpretation efforts in the early part of the exploration and appraisal cycle. Several case studies were used to highlight that subtle fluid effects can only be extracted from the seismic data after careful assessment of the lithology response. These case studies cover a wide geography and variable geology and demonstrate that the techniques we tested are transferable and applicable across many different oil and gas provinces. The use of lithology stacks has many benefits. It allows interpretation on a single stack rather than many different offset or angle stacks. A lithology stack provides a robust, objective framework for lithostratigraphic interpretation and can be calibrated to offset wells when available. They are conceptually simple, repeatable, and transferable, allowing close cooperation across the different subsurface disciplines.

Basin-wide rock-physics analysis in Campeche Basin, Gulf of Mexico — Phase II: Reservoir rock and fluid properties

2021 ◽  
Vol 40 (10) ◽  
pp. 716-722
Author(s):  
Yangjun (Kevin) Liu ◽  
Michelle Ellis ◽  
Mohamed El-Toukhy ◽  
Jonathan Hernandez
Keyword(s):  
Oil And Gas ◽  
Rock Physics ◽  
Clay Content ◽  
American Petroleum Institute ◽  
P Wave ◽  
Reservoir Rock ◽  
Gas Oil ◽  
Amplitude Variation With Offset ◽  
Fluid Properties ◽  
The Impact

We present a basin-wide rock-physics analysis of reservoir rocks and fluid properties in Campeche Basin. Reservoir data from discovery wells are analyzed in terms of their relationship between P-wave velocity, density, porosity, clay content, Poisson's ratio (PR), and P-impedance (IP). The fluid properties are computed by using in-situ pressure, temperature, American Petroleum Institute gravity, gas-oil ratio, and volume of gas, oil, and water. Oil- and gas-saturated reservoir sands show strong PR anomalies compared to modeled water sand at equivalent depth. This suggests that PR anomalies can be used as a direct hydrocarbon indicator in the Tertiary sands in Campeche Basin. However, false PR anomalies due to residual gas or oil exist and compose about 30% of the total anomalies. The impact of fluid properties on IP and PR is calibrated using more than 30 discovery wells. These calibrated relationships between fluid properties and PR can be used to guide or constrain amplitude variation with offset inversion for better pore fluid discrimination.

Integrated geological and geophysical interpretation case study, and Lamé rock parameter extractions using AVO analysis on the Blackfoot 3C‐3D seismic data, southern Alberta, Canada

Geophysics ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 27-37 ◽  
Author(s):  
Jocelyn Dufour ◽  
Jason Squires ◽  
William N. Goodway ◽  
Andy Edmunds ◽  
Ian Shook
Keyword(s):  
Cross Sections ◽  
Seismic Data ◽  
Oil And Gas ◽  
Well Log ◽  
Amplitude Variation With Offset ◽  
Incised Valley ◽  
Geophysical Interpretation ◽  
Porous Sandstone ◽  
Incised Valleys ◽  
Geological Facies

Blackfoot field, southeast of Calgary, Alberta, Canada, has produced oil and gas from a Glauconitic compound incised‐valley system. The Glauconitic compound incised valley has three cycles of incision and valley fill: lower, lithic, and upper incised valleys. The upper and lower incised valleys are the main reservoirs. The geophysical interpretation of compressional PP‐seismic data resulted in the definition of the compound‐valley extent, and in the mapping of the upper and lower incised valleys. A stratigraphic well‐log template was built using the most significant lithological information and well logs. To integrate both geological and geophysical interpretations, the well log cross‐sections and corresponding depth‐converted seismic were superimposed. Furthermore, a detailed geological facies interpretation of the upper and lower incised valleys was undertaken and incorporated. A good correlation was found between the interpreted geological facies and the seismic data response. Information about the nature of the fill within the compound valley was gained from the integration of the PP‐ and PS‐wave interpretations. However, this is limited to Vp/Vs analyses on given intervals. Amplitude‐variation‐with‐offset analysis of the PP‐data was run to discriminate lithology and pore‐fluid saturates. The products of the Lamé rock parameters, incompressibility (λ) and rigidity (μ), with density (ρ) were extracted from seismic inversions for P‐ and S‐impedances. The extraction of λ ρ and μρ showed the presence of gas‐bearing porous sandstone within the Glauconitic incised‐valley system.

Seismic reservoir characterization of the Bone Spring and Wolfcamp Formations in the Delaware Basin: Challenges and uncertainty in characterization using rock physics — A case study: Part 2

2020 ◽  
Vol 8 (4) ◽  
pp. T1057-T1069
Author(s):  
Ritesh Kumar Sharma ◽  
Satinder Chopra ◽  
Larry Lines
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Well Log ◽  
Data Set ◽  
Frequency Model ◽  
Log Data ◽  
Delaware Basin ◽  
Seismic Reservoir

The discrimination of fluid content and lithology in a reservoir is important because it has a bearing on reservoir development and its management. Among other things, rock-physics analysis is usually carried out to distinguish between the lithology and fluid components of a reservoir by way of estimating the volume of clay, water saturation, and porosity using seismic data. Although these rock-physics parameters are easy to compute for conventional plays, there are many uncertainties in their estimation for unconventional plays, especially where multiple zones need to be characterized simultaneously. We have evaluated such uncertainties with reference to a data set from the Delaware Basin where the Bone Spring, Wolfcamp, Barnett, and Mississippian Formations are the prospective zones. Attempts at seismic reservoir characterization of these formations have been developed in Part 1 of this paper, where the geologic background of the area of study, the preconditioning of prestack seismic data, well-log correlation, accounting for the temporal and lateral variation in the seismic wavelets, and building of robust low-frequency model for prestack simultaneous impedance inversion were determined. We determine the challenges and the uncertainty in the characterization of the Bone Spring, Wolfcamp, Barnett, and Mississippian sections and explain how we overcame those. In the light of these uncertainties, we decide that any deterministic approach for characterization of the target formations of interest may not be appropriate and we build a case for adopting a robust statistical approach. Making use of neutron porosity and density porosity well-log data in the formations of interest, we determine how the type of shale, volume of shale, effective porosity, and lithoclassification can be carried out. Using the available log data, multimineral analysis was also carried out using a nonlinear optimization approach, which lent support to our facies classification. We then extend this exercise to derived seismic attributes for determination of the lithofacies volumes and their probabilities, together with their correlations with the facies information derived from mud log data.

A successful qualitative and quantitative integrated interpretation of Lower Miocene wells and seismic data in Salina del Istmo Basin, Mexico

2021 ◽  
Vol 40 (12) ◽  
pp. 897-904
Author(s):  
Manuel González-Quijano ◽  
Gregor Baechle ◽  
Miguel Yanez ◽  
Freddy Obregon ◽  
Carmen Vito ◽  
...  
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Reservoir Rock ◽  
Amplitude Variation With Offset ◽  
Volcanic Material ◽  
Qualitative And Quantitative ◽  
Rock Types ◽  
Deep Waters ◽  
Well Data ◽  
Gulf Of Mexico Basin

The study area is located in middepth to deep waters of the Salina del Istmo Basin where Repsol operates Block 29. The objective of this work is to integrate qualitative and quantitative interpretations of rock and seismic data to predict lithology and fluid of the Early Miocene prospects. The seismic expression of those prospects differs from age-equivalent well-studied analog fields in the U.S. Gulf of Mexico Basin due to the mineralogically complex composition of abundant extrusive volcanic material. Offset well data (i.e., core, logs, and cuttings) were used to discriminate lithology types and to quantify mineralogy. This analysis served as input for developing a new rock-physics framework and performing amplitude variation with offset (AVO) modeling. The results indicate that the combination of intercept and gradient makes it possible to discriminate hydrocarbon-filled (AVO class II and III) versus nonhydrocarbon-filled rocks (AVO class 0 and IV). Different lithologies within hydrocarbon-bearing reservoirs cannot be discriminated as the gradient remains negative for all rock types. However, AVO analysis allows discrimination of three different reservoir rock types in water-bearing cases (AVO class 0, I, and IV). These conclusions were obtained during studies conducted in 2018–2019 and were used in prospect evaluation to select drilling locations leading to two wildcat discoveries, the Polok and Chinwol prospects, drilled in Block 29 in 2020.

Seismic reservoir characterization of Duvernay shale with quantitative interpretation and induced seismicity considerations — A case study

2017 ◽  
Vol 5 (2) ◽  
pp. T185-T197 ◽  
Author(s):  
Satinder Chopra ◽  
Ritesh Kumar Sharma ◽  
Amit Kumar Ray ◽  
Hossein Nemati ◽  
Ray Morin ◽  
...  
Keyword(s):  
Media Coverage ◽  
Induced Seismicity ◽  
Oil And Gas ◽  
Reservoir Characterization ◽  
Learning Experience ◽  
Rock Physics ◽  
Quantitative Interpretation ◽  
Gas Generation ◽  
Gaseous Hydrocarbon

The Devonian Duvernay Formation in northwest central Alberta, Canada, has become a hot play in the past few years due to its richness in liquid and gaseous hydrocarbon resources. The oil and gas generation in this shale formation made it the source rock for many oil and gas fields in its vicinity. We attempt to showcase the characterization of Duvernay Formation using 3D multicomponent seismic data and integrating it with the available well log and other relevant data. This has been done by deriving rock-physics parameters (Young’s modulus and Poisson’s ratio) through deterministic simultaneous and joint impedance inversion, with appropriate quantitative interpretation. In particular, we determine the brittleness of the Duvernay interval, which helps us determine the sweet spots therein. The scope of this characterization exercise was extended to explore the induced seismicity observed in the area (i.e., earthquakes of magnitude [Formula: see text]) that is perceived to be associated with hydraulic fracture stimulation of the Duvernay. This has been a cause of media coverage lately. We attempt to integrate our results with the induced seismicity data available in the public domain and elaborate on our learning experience gained so far.

Prediction of elastic properties using seismic prestack inversion and neural network analysis

2015 ◽  
Vol 3 (2) ◽  
pp. T57-T68 ◽  
Author(s):  
Islam A. Mohamed ◽  
Hamed Z. El-Mowafy ◽  
Mohamed Fathy
Keyword(s):  
Neural Network ◽  
Network Analysis ◽  
Seismic Data ◽  
Seismic Inversion ◽  
Neural Network Analysis ◽  
Inversion Result ◽  
Amplitude Variation With Offset ◽  
Well Control ◽  
Prestack Inversion

The use of artificial intelligence algorithms to solve geophysical problems is a recent development. Neural network analysis is one of these algorithms. It uses the information from multiple wells and seismic data to train a neural network to predict properties away from the well control. Neural network analysis can significantly improve the seismic inversion result when the outputs of the inversion are used as external attributes in addition to regular seismic attributes for training the network. We found that integration of prestack inversion and neural network analysis can improve the characterization of a late Pliocene gas sandstone reservoir. For inversion, the input angle stacks was conditioned to match the theoretical amplitude-variation-with-offset response. The inversion was performed using a deterministic wavelet set. Neural network analysis was then used to enhance the [Formula: see text], [Formula: see text], and density volumes from the inversion. The improvement was confirmed by comparisons with logs from a blind well.

Quantifying the uncertainty in an AVO interpretation

Geophysics ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 117-125 ◽  
Author(s):  
Richard T. Houck
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Reflection Coefficients ◽  
Amplitude Variation ◽  
Data Set ◽  
Amplitude Variation With Offset ◽  
Full Characterization ◽  
The North ◽  
The North Sea

Lithologic interpretations of amplitude variation with offset (AVO) information are ambiguous both because different lithologies occupy overlapping ranges of elastic properties, and because angle‐dependent reflection coefficients estimated from seismic data are uncertain. This paper presents a method for quantifying and combining these two components of uncertainty to get a full characterization of the uncertainty associated with an AVO‐based lithologic interpretation. The result of this approach is a compilation of all the lithologies that are consistent with the observed AVO behavior, along with a probability of occurrence for each lithology. A 2‐D line from the North Sea illustrates how the method might be applied in practice. For any data set, the interaction between the geologic and measurement components of uncertainty may significantly affect the overall uncertainty in a lithologic interpretation.

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.

Modeling studies of interference reflections in thin‐layered media bounded by coal seams

Geophysics ◽  
1992 ◽  
Vol 57 (9) ◽  
pp. 1209-1216 ◽  
Author(s):  
Lawrence M. Gochioco
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Oil And Gas ◽  
Close Correlation ◽  
Destructive Interference ◽  
Modeling Studies ◽  
Velocity Information ◽  
Interpretation Process ◽  
Ricker Wavelet ◽  
Sonic Logs

High‐resolution seismic data collected over a major U.S. coal basin indicated potential complex problems associated with interference reflections. These problems differed from those normally encountered in the exploration of oil and gas because of differences in the geologic boundary conditions. Modeling studies were conducted to investigate the effects of overlapping primary reflections and the composite reflection that result from stacking individual wavelets. A modified empirical formula of Lindseth’s linear relationship between acoustic impedance and velocity is used to extrapolate velocity information from density logs to provide appropriate geophysical properties for modeling. The synthetic seismograms generated from density and synthetic sonic logs correlated well with the processed seismic data. A 150-Hz Ricker wavelet is used to convolve with the computer models, and the models showed that certain anomalous composite reflections result from the superposition of overlapping primary reflections. Depending on the traveltime delay of latter primary reflections, constructive or destructive interference could significantly alter the signature of the initial reflection associated with the bed of interest, which may lead to misinterpretations if not properly identified. The stratigraphic modeling technique further enhances the interpretation process and shows a close correlation with the seismic data, suggesting that more precise analytical methods need to be used to interpret, sometimes complex, high‐resolution seismic data.

Seismic reservoir characterization of Utica-Point Pleasant shale with efforts at fracability evaluation — Part 2: A case study

2018 ◽  
Vol 6 (2) ◽  
pp. T325-T336 ◽  
Author(s):  
Ritesh Kumar Sharma ◽  
Satinder Chopra ◽  
James Keay ◽  
Hossein Nemati ◽  
Larry Lines
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Rock Physics ◽  
Well Log ◽  
X Ray Diffraction ◽  
Impedance Inversion ◽  
Seismic Reservoir ◽  
Petrophysical Modeling

The Utica Formation in eastern Ohio possesses all the prerequisites for being a successful unconventional play. Attempts at seismic reservoir characterization of the Utica Formation have been discussed in part 1, in which, after providing the geologic background of the area of study, the preconditioning of prestack seismic data, well-log correlation, and building of robust low-frequency models for prestack simultaneous impedance inversion were explained. All these efforts were aimed at identification of sweet spots in the Utica Formation in terms of organic richness as well as brittleness. We elaborate on some aspects of that exercise, such as the challenges we faced in the determination of the total organic carbon (TOC) volume and computation of brittleness indices based on mineralogical and geomechanical considerations. The prediction of TOC in the Utica play using a methodology, in which limited seismic as well as well-log data are available, is demonstrated first. Thereafter, knowing the nonexistence of the universally accepted indicator of brittleness, mechanical along with mineralogical attempts to extract the brittleness information for the Utica play are discussed. Although an attempt is made to determine brittleness from mechanical rock-physics parameters (Young’s modulus and Poisson’s ratio) derived from seismic data, the available X-ray diffraction data and regional petrophysical modeling make it possible to determine the brittleness index based on mineralogical data and thereafter be derived from seismic data.

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