scholarly journals Pressure and fluid saturation prediction in a multicomponent reservoir using combined seismic and electromagnetic imaging

Geophysics ◽  
2003 ◽  
Vol 68 (5) ◽  
pp. 1580-1591 ◽  
Author(s):  
G. Michael Hoversten ◽  
Roland Gritto ◽  
John Washbourne ◽  
Tom Daley
Keyword(s):  
Electrical Conductivity ◽  
Water Saturation ◽  
Saturation Pressure ◽  
Shear Velocity ◽  
Velocity Shear ◽  
Rock Properties ◽  
Velocity Change ◽  
Archie’S Law ◽  
Fluid Saturation ◽  
Compressional Velocity

This paper presents a method for combining seismic and electromagnetic (EM) measurements to predict changes in water saturation, pressure, and CO2 gas/oil ratio in a reservoir undergoing CO2 flood. Crosswell seismic and EM data sets taken before and during CO2 flooding of an oil reservoir are inverted to produce crosswell images of the change in compressional velocity, shear velocity, and electrical conductivity during a CO2 injection pilot study. A rock‐properties model is developed using measured log porosity, fluid saturations, pressure, temperature, bulk density, sonic velocity, and electrical conductivity. The parameters of the rock‐properties model are found by an L1‐norm simplex minimization of predicted and observed differences in compressional velocity and density. A separate minimization, using Archie's law, provides parameters for modeling the relations between water saturation, porosity, and electrical conductivity. The rock‐properties model is used to generate relationships between changes in geophysical parameters and changes in reservoir parameters. Electrical conductivity changes are directly mapped to changes in water saturation; estimated changes in water saturation are used along with the observed changes in shear‐wave velocity to predict changes in reservoir pressure. The estimation of the spatial extent and amount of CO2 relies on first removing the effects of the water saturation and pressure changes from the observed compressional velocity changes, producing a residual compressional velocity change. This velocity change is then interpreted in terms of increases in the CO2/oil ratio. Resulting images of the CO2/oil ratio show CO2‐rich zones that are well correlated to the location of injection perforations, with the size of these zones also correlating to the amount of injected CO2. The images produced by this process are better correlated to the location and amount of injected CO2 than are any of the individual images of change in geophysical parameters.

scholarly journals Petrophysical interpretation and fluid substitution modelling of the upper shallow marine sandstone reservoirs in the Bredasdorp Basin, offshore South Africa

2019 ◽  
Vol 10 (2) ◽  
pp. 783-803
Author(s):  
Moses Magoba ◽  
Mimonitu Opuwari
Keyword(s):  
South Africa ◽  
Water Saturation ◽  
Shear Velocity ◽  
Acoustic Properties ◽  
Rock Properties ◽  
Fluid Substitution ◽  
Shallow Marine ◽  
Fluid Saturation ◽  
Sandstone Reservoirs ◽  
Gassmann Fluid Substitution

Abstract The fluid substitution method is used for predicting elastic properties of reservoir rocks and their dependence on pore fluid and porosity. This method makes it possible to predict changes in elastic response of a rock saturation with different fluids. This study focused on the Upper Shallow Marine sandstone reservoirs of five selected wells (MM1, MM2, MM3, MM4, and MM5) in the Bredasdorp Basin, offshore South Africa. The integration of petrophysics and rock physics (Gassmann fluid substitution) was applied to the upper shallow marine sandstone reservoirs for reservoir characterisation. The objective of the study was to calculate the volume of clay, porosity, water saturation, permeability, and hydrocarbon saturation, and the application of the Gassmann fluid substitution modelling to determine the effect of different pore fluids (brine, oil, and gas) on acoustic properties (compressional velocity, shear velocity, and density) using rock frame properties. The results showed average effective porosity ranging from 8.7% to 16.6%, indicating a fair to good reservoir quality. The average volume of clay, water saturation, and permeability values ranged from 8.6% to 22.3%, 18.9% to 41.6%, and 0.096–151.8 mD, respectively. The distribution of the petrophysical properties across the field was clearly defined with MM2 and MM3 revealing good porosity and MM1, MM4, and MM5 revealing fair porosity. Well MM4 revealed poor permeability, while MM3 revealed good permeability. The fluid substitution affected rock property significantly. The primary velocity, Vp, slightly decreased when brine was substituted with gas in wells MM1, MM2, MM3, and MM4. The shear velocity, Vs, remained unaffected in all the wells. This study demonstrated how integration of petrophysics and fluid substitution can help to understand the behaviour of rock properties in response to fluid saturation changes in the Bredasdorp Basin. The integration of these two disciplines increases the obtained results’ quality and reliability.

Cross-property relations between electrical conductivity and the seismic velocity of rocks

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. E193-E204 ◽  
Author(s):  
José M. Carcione ◽  
Bjørn Ursin ◽  
Janniche I. Nordskag
Keyword(s):  
Electrical Conductivity ◽  
Constitutive Equations ◽  
Seismic Velocity ◽  
Refraction Index ◽  
Rock Properties ◽  
Index Method ◽  
Archie’S Law ◽  
Property Relations ◽  
Backus Averaging ◽  
Self Similar

Cross-property relations are useful when some rock properties can be measured more easily than other properties. Relations between electrical conductivity and seismic velocity, stiffness moduli, and density can be obtained by expressing the porosity in terms of those properties. There are many possible ways to combine the constitutive equations to obtain a relation, each one representing a given type of rock. The relations depend on the assumptions to obtain the constitutive equations. In the electromagnetic case, the equations involve Archie’s law and its modifications for a conducting frame, the Hashin-Shtrikman (HS) bounds, and the self-similar and complex refraction-index method (CRIM) models. In the elastic case, the stress-strain relations are mainly based on the time-average equation, the HS bounds, and the Gassmann equation. Also, expressions for dry rocks and for anisotropic media, using Backus averaging, are analyzed. The relations are applied to a shale saturated with brine (overburden) and to a sandstone saturated with oil (reservoir). Tests with sections of a North Sea well log show that the best fit is given by the relation between the Gassmann velocity and the CRIM, self-similar, and Archie models for the conductivity.

AVO in transversely Isotropic media—An overview

Geophysics ◽  
1994 ◽  
Vol 59 (5) ◽  
pp. 775-781 ◽  
Author(s):  
J. P. Blangy
Keyword(s):  
Transversely Isotropic ◽  
Shear Velocity ◽  
Velocity Shear ◽  
Type I ◽  
Amplitude Variation With Offset ◽  
Type Iii ◽  
Transversely Isotropic Media ◽  
Isotropic Media ◽  
Compressional Velocity ◽  
Ti Media

The amplitude variation with offset (AVO) responses of elastic transversely isotropic media are sensitive to contrasts in both of Thomsen’s anisotropic parameters δ and ε. The equation describing P-P reflections indicates that the smaller the contrasts in isotropic properties (compressional velocity, shear velocity, and density) and the larger the contrasts in δ and ε across an interface of reflection, the greater the effects of anisotropy on the AVO signature. Contrasts in δ are most important under small‐to‐medium angles of incidence as previously described by Banik (1987), while contrasts in ε can have a strong influence on amplitudes for the larger angles of incidence commonly encountered in exploration (20 degrees and beyond). Consequently, using Rutherford and Williams’ AVO classification of isotropic gas sands, type I gas sands overlain by a transversely isotropic (TI) shale exhibit a larger decrease in AVO than if the shale had been isotropic, and type III gas sands overlain by a transversely isotropic (TI) shale exhibit a larger increase in AVO than if the shale had been isotropic. Furthermore, it is possible for a “type III” isotropic water sand to exhibit an “unexpected) increase in AVO if the overlying shale is sufficiently anisotropic. More quantitative AVO interpretations in TI media require considerations of viscoelastic TI in addition to elastic TI and lead to complicated integrated earth models. However, when elastic and viscoelastic TI have the same axis of symmetry in a shale overlying an isotropic sand, both elastic and viscoelastic TI affect the overall AVO response in the same direction by constructively increasing/decreasing the isotropic component of the AVO response. Continued efforts in this area will lead to more realistic reservoir models and hopefully answer some of the unexplained pitfalls in AVO interpretation.

Direct reservoir parameter estimation using joint inversion of marine seismic AVA and CSEM data

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. C1-C13 ◽  
Author(s):  
G. Michael Hoversten ◽  
Florence Cassassuce ◽  
Erika Gasperikova ◽  
Gregory A. Newman ◽  
Jinsong Chen ◽  
...  
Keyword(s):  
Water Saturation ◽  
Joint Inversion ◽  
Hydrocarbon Exploration ◽  
Rock Properties ◽  
Parameter Estimates ◽  
Angle Of Incidence ◽  
Model Errors ◽  
Inversion Algorithm ◽  
Fluid Saturation ◽  
Reservoir Parameter

Accurately estimating reservoir parameters from geophysical data is vitally important in hydrocarbon exploration and production. We have developed a new joint-inversion algorithm to estimate reservoir parameters directly, using both seismic amplitude variation with angle of incidence (AVA) data and marine controlled-source electromagnetic (CSEM) data. Reservoir parameters are linked to geophysical parameters through a rock-properties model. Errors in the parameters of the rock-properties model introduce errors of comparable size in the reservoir-parameter estimates produced by joint inversion. Tests of joint inversion on synthetic 1D models demonstrate improved fluid saturation and porosity estimates for joint AVA-CSEM data inversion (compared with estimates from AVA or CSEM inversion alone). A comparison of inversions of AVA data, CSEM data, and joint AVA-CSEM data over the North Sea Troll field, at a location for which we have well control, shows that the joint inversion produces estimates of gas saturation, oil saturation, and porosity that are closest (as measured by the rms difference, the [Formula: see text] norm of the difference, and net values over the interval) to the logged values. However, CSEM-only inversion provides the closest estimates of water saturation.

scholarly journals DETERMINATION CONVENTIONAL ROCK PROPERTIES FROM LOG DATA & CORE DATA FOR UPPER NUBIAN SANDSTONE FORMATION OF ABU ATTIFEL FIELD

2019 ◽  
Vol 2 (1) ◽  
pp. 29-37
Author(s):  
Adel Alabeed ◽  
Zeyad Ibrahim ◽  
Emhemed Alfandi
Keyword(s):  
Water Saturation ◽  
Rock Properties ◽  
Well Log ◽  
Log Data ◽  
Nubian Sandstone ◽  
Core Data ◽  
Hydrocarbon Reservoir ◽  
Fluid Saturation ◽  
Volume Porosity ◽  
Sandstone Formation

A reservoir is a subsurface rock that has effective porosity and permeability which usually contains commercially exploitable quantity of hydrocarbon. Reservoir characterization is undertaken to determine its capability to both store and transmit fluid. Petrophysical well log and core data, in this paper, were integrated in an analysis of the reservoir characteristics by selecting of three productive wells. The selected wells are located at Abu Attifel field in Libya for Upper Nubian Sandstone formation at depth varied form 12921 to14330 ft. The main aim of this study is to compare the laboratory measurement of core data with that obtained from well log data in order to determine reservoir properties such as shale volume, porosity (Φ), permeability (K), fluid saturation, net pay thickness. The plots of porosity logs and core porosity versus depth for the three wells revealed significant similarity in the porosity values. The average volume of shale for the reservoir was determined to be 22.5%, and average permeability values of the three wells are above 150 md, while porosity values ranged from 9 to 11%. Low water saturation 13 to 22% in the three wells indicates the wettability of the reservoir is water-wet.

scholarly journals Log-based prediction of pore pressure and its relationship to compressional velocity, shear velocity and Poisson’s ratio in gas reservoirs; Case study from selected gas wells in Iran

2021 ◽  
Vol 266 ◽  
pp. 01015
Author(s):  
E. R. Nikou ◽  
H. Aghaei ◽  
M. Ghaedi ◽  
H. Jafarpour
Keyword(s):  
Fluid Pressure ◽  
Shear Velocity ◽  
Oil Reservoirs ◽  
Velocity Shear ◽  
Fluid Type ◽  
Gas Wells ◽  
Pore Fluid Pressure ◽  
Gas Reservoirs ◽  
Compressional Velocity

A precise identification of pore fluid pressure (PP) is of great significance, specifically, in terms of drilling safety and reservoir management. Despite numerous work have been carried out for prediction of PP in oil reservoirs, but there still exists a tangible lack of such work in gas hosting rocks. The present study aims to discuss and evaluate the application of a number of existing methods for prediction of PP in two selected giant carbonate gas reservoirs in south Iran. For this purpose, PP was first estimated based on the available conventional log data and later compared with the PP suggested by Reservoir Formation Test (RFT) and other bore data. At the end, it has been revealed that while PP prediction is highly dependent on the type of litho logy in carbonates, the effect of fluid type is negligible. Moreover, the velocity correlations work more efficiently for the pure limestone/dolomite reservoirs compared with the mixed ones.

scholarly journals The Dependence of Electrical Resistivity-Saturation Relationships on Multiphase Flow Instability

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Zoulin Liu ◽  
Stephen M. J. Moysey
Keyword(s):  
Electrical Resistivity ◽  
Multiphase Flow ◽  
Light Transmission ◽  
Flow Instability ◽  
Water Saturation ◽  
Bond Number ◽  
Smooth Transition ◽  
Transmission Method ◽  
Archie’S Law ◽  
Fluid Saturation

We investigate the relationship between apparent electrical resistivity and water saturation during unstable multiphase flow. We conducted experiments in a thin, two-dimensional tank packed with glass beads, where Nigrosine dyed water was injected uniformly along one edge to displace mineral oil. The resulting patterns of fluid saturation in the tank were captured on video using the light transmission method, while the apparent resistivity of the tank was continuously measured. Different experiments were performed by varying the water application rate and orientation of the tank to control the generalized Bond number, which describes the balance between viscous, capillary, and gravity forces that affect flow instability. We observed the resistivity index to gradually decrease as water saturation increases in the tank, but sharp drops occurred as individual fingers bridged the tank. The magnitude of this effect decreased as the displacement became increasingly unstable until a smooth transition occurred for highly unstable flows. By analyzing the dynamic data using Archie’s law, we found that the apparent saturation exponent increases linearly between approximately 1 and 2 as a function of generalized Bond number, after which it remained constant for unstable flows with a generalized Bond number less than −0.106.

Lithology discrimination from physical rock properties

Geophysics ◽  
2002 ◽  
Vol 67 (2) ◽  
pp. 573-581 ◽  
Author(s):  
Miguel Bosch ◽  
Maaria Zamora ◽  
Widya Utama
Keyword(s):  
Discriminant Analysis ◽  
Physical Properties ◽  
Survey Methods ◽  
Mass Density ◽  
Shear Velocity ◽  
Velocity Shear ◽  
Rock Properties ◽  
Crustal Rocks ◽  
Graphic Analysis ◽  
The Media

The estimation of lithology from multiple geophysical survey methods needs to be addressed to develop advanced tomographic methods. An initial requirement for lithology discrimination is that lithology should be discriminable from the media properties physically related to the geophysical observations. To test this condition for different combinations of the most common crustal rocks, we performed several lithology discrimination exercises on rock samples under laboratory conditions. The physical properties included mass density, compressional velocity, shear velocity, electric conductivity, thermal conductivity, and magnetic susceptibility. A categorical description of the sample lithology was followed; hence, the inference consisted of predicting the sample rock category (lithotype) membership. The joint information provided by the physical properties of the rocks allowed us to discriminate the sample lithotype correctly, with an overall success rate of 100% in the most favorable situation and over 85% in the least favorable situation. We obtained successful classification results for a variety of common lithotypes (granite, gabbro, limestone, tuff, marble, basalt, and gneiss) using three common classification methods: clustering analysis, Gaussian classification, and discriminant analysis. Although discrimination was positive with each of these multivariate classification techniques, discriminant analysis showed some advantages for the classification and graphic analysis of the data. These results support our postulate that lithology can be estimated reliably if multiple geophysical observations are considered jointly.

Digital Rock Typing DRT Algorithm Formulation with Optimal Supervised Semantic Segmentation

2022 ◽  
Author(s):  
Omar Alfarisi ◽  
Djamel Ouzzane ◽  
Mohamed Sassi ◽  
TieJun Zhang
Keyword(s):  
Carbonate Rock ◽  
Chemical Properties ◽  
Rock Physics ◽  
Semantic Segmentation ◽  
Rock Properties ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Rock Types ◽  
Fluid Saturation ◽  
Rock Typing

<p><a></a>Each grid block in a 3D geological model requires a rock type that represents all physical and chemical properties of that block. The properties that classify rock types are lithology, permeability, and capillary pressure. Scientists and engineers determined these properties using conventional laboratory measurements, which embedded destructive methods to the sample or altered some of its properties (i.e., wettability, permeability, and porosity) because the measurements process includes sample crushing, fluid flow, or fluid saturation. Lately, Digital Rock Physics (DRT) has emerged to quantify these properties from micro-Computerized Tomography (uCT) and Magnetic Resonance Imaging (MRI) images. However, the literature did not attempt rock typing in a wholly digital context. We propose performing Digital Rock Typing (DRT) by: (1) integrating the latest DRP advances in a novel process that honors digital rock properties determination, while; (2) digitalizing the latest rock typing approaches in carbonate, and (3) introducing a novel carbonate rock typing process that utilizes computer vision capabilities to provide more insight about the heterogeneous carbonate rock texture.<br></p>

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