NO346380B1 - Fluid identification and saturation estimation using CSEM and seismic data - Google Patents
Fluid identification and saturation estimation using CSEM and seismic data Download PDFInfo
- Publication number
- NO346380B1 NO346380B1 NO20191431A NO20191431A NO346380B1 NO 346380 B1 NO346380 B1 NO 346380B1 NO 20191431 A NO20191431 A NO 20191431A NO 20191431 A NO20191431 A NO 20191431A NO 346380 B1 NO346380 B1 NO 346380B1
- Authority
- NO
- Norway
- Prior art keywords
- resistivity
- saturation
- data
- values
- acoustic impedance
- Prior art date
Links
- 239000012530 fluid Substances 0.000 title claims description 72
- 238000000034 method Methods 0.000 claims description 65
- 239000011435 rock Substances 0.000 claims description 40
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 40
- 239000011159 matrix material Substances 0.000 claims description 22
- 239000000523 sample Substances 0.000 claims description 21
- 230000015572 biosynthetic process Effects 0.000 claims description 18
- 238000005755 formation reaction Methods 0.000 claims description 18
- 238000005259 measurement Methods 0.000 claims description 14
- 239000011148 porous material Substances 0.000 claims description 9
- 238000010586 diagram Methods 0.000 claims description 8
- 239000007788 liquid Substances 0.000 claims description 7
- 230000004044 response Effects 0.000 claims description 4
- 229920006395 saturated elastomer Polymers 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 3
- 238000005056 compaction Methods 0.000 claims description 3
- 230000035800 maturation Effects 0.000 claims description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 12
- 229930195733 hydrocarbon Natural products 0.000 description 12
- 150000002430 hydrocarbons Chemical class 0.000 description 12
- 239000007789 gas Substances 0.000 description 5
- 239000013505 freshwater Substances 0.000 description 3
- 238000011065 in-situ storage Methods 0.000 description 3
- 229910052500 inorganic mineral Inorganic materials 0.000 description 3
- 239000011707 mineral Substances 0.000 description 3
- FAPWRFPIFSIZLT-UHFFFAOYSA-M Sodium chloride Chemical compound [Na+].[Cl-] FAPWRFPIFSIZLT-UHFFFAOYSA-M 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 239000008398 formation water Substances 0.000 description 2
- 230000008014 freezing Effects 0.000 description 2
- 238000007710 freezing Methods 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000000704 physical effect Effects 0.000 description 2
- 239000011780 sodium chloride Substances 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000005481 NMR spectroscopy Methods 0.000 description 1
- 102100027611 Rho-related GTP-binding protein RhoB Human genes 0.000 description 1
- 101150054980 Rhob gene Proteins 0.000 description 1
- 235000015076 Shorea robusta Nutrition 0.000 description 1
- 244000166071 Shorea robusta Species 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000003190 augmentative effect Effects 0.000 description 1
- 239000012267 brine Substances 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 239000004927 clay Substances 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 238000013016 damping Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 210000003722 extracellular fluid Anatomy 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000011005 laboratory method Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 239000003921 oil Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 150000003839 salts Chemical class 0.000 description 1
- 239000013535 sea water Substances 0.000 description 1
- 239000013049 sediment Substances 0.000 description 1
- HPALAKNZSZLMCH-UHFFFAOYSA-M sodium;chloride;hydrate Chemical compound O.[Na+].[Cl-] HPALAKNZSZLMCH-UHFFFAOYSA-M 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000012876 topography Methods 0.000 description 1
- 239000011800 void material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
- E21B49/08—Obtaining fluid samples or testing fluids, in boreholes or wells
- E21B49/087—Well testing, e.g. testing for reservoir productivity or formation parameters
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
- G01V1/44—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging using generators and receivers in the same well
- G01V1/48—Processing data
- G01V1/50—Analysing data
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/18—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for well-logging
- G01V3/30—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for well-logging operating with electromagnetic waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/624—Reservoir parameters
- G01V2210/6244—Porosity
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Geology (AREA)
- Engineering & Computer Science (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geophysics (AREA)
- Environmental & Geological Engineering (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Mining & Mineral Resources (AREA)
- Electromagnetism (AREA)
- Acoustics & Sound (AREA)
- Fluid Mechanics (AREA)
- Geochemistry & Mineralogy (AREA)
- Geophysics And Detection Of Objects (AREA)
Description
Description
Title
Fluid identification and saturation estimation using CSEM and seismic data
The object of the invention
The present invention relates generally to the field of exploration geophysics, and more particularly to identification and characterisation of potential hydrocarbon (oil, gas, and natural gas liquids) or CO2 storage reservoirs in onshore and offshore sedimentary basins, using combined seismic and electromagnetic geophysical data acquired onshore or offshore. The invention also relates to subsurface formation interval sonic velocity, bulk density, and electrical resistivity measured from borehole logs in a well as means to calibrate the seismic and electromagnetic geophysical data.
Background for the invention
The acquisition and inversion of electromagnetic data has in recent years become a valuable tool in investigating potential hydrocarbon-bearing formations. Controlled-source electromagnetic (CSEM) data is often combined with other measurement data, such as seismic, gravity, magnetotelluric (MT) survey or nearby well-logs to mention a few. In most CSEM surveying acquisitions, a CSEM system comprises an electromagnetic emitter or antenna, that is either pulled from a vessel, stationary in the body of water or on the seabed, and likewise a number of electromagnetic receivers that are fixed on the seabed or towed from a vessel or stationary in the body of water. The receivers record variations in electrical resistance depending on variations in source signal, offset between the source and receiver and the geological properties of rock layers, including their inherent electrical resistivity properties. For instance, a hydrocarbon-bearing layer will exhibit a higher electrical resistance compared to the seawater or overburden of sediment or rock. The CSEM Inversion techniques have been developed to optimise the parameters of a model to find the best fit between the calculated value and the measured data while constraining the model employing the measured data.
Seismic surveys, when used in combination with other available geophysical, borehole, and geological data, provide useful information about the structure and distribution of subsurface rock properties and their interstitial fluids. Oil companies employ interpretation of such seismic data for selecting the sites to drill oil and gas exploratory and development wells. The seismic surveys while providing maps of geological structures also yield useful information for rock typing, fluid identification and quantification.
When borehole logs are available from nearby wells, seismic survey and CSEM data can be enhanced and calibrated by combining it with the log data. Compared to the CSEM resistivity, the log resistivity that is measured is usually assumed to be the horizontal component, primarily due to the design of the borehole tool. On the other hand, the log sonic transit time that is measured in a well is usually assumed to be the vertical component, again due to the design of the borehole tool.
Prior art modelling methods are based on applying resistance directly from CSEM inversion results, and inserting these into an appropriate saturation-resistivity relation, such as Archie's equation (Archie 1942) or similar. Data inversion provides an estimate of physical properties by way of updating an initial model based upon available measured data and other prior information from a given area. In brief, Archie's equation is an empirical quantitative relationship between porosity, electrical resistivity, and brine saturation of rocks. The equation is a basis for modern well-log interpretation as it relates borehole electrical resistivity measurements to hydrocarbon saturations. There are various forms of Archie's equation, such as the following general form:
where, Sw is water saturation, Φ is porosity, Rw is formation water resistivity, Rt is acquired total resistivity, ‘a’ is tortuosity constant (usually about 0.6 for sandstone), m is cementation factor (usually about 2), and n is saturation exponent (usually about 2).
Using porosity derived from the Wyllie’s equation applied on the seismic-derived velocity, total resistivity from the CSEM and assuming the water resistivity (and exponents in Archie's equation) are known, the fluid saturation (Sfl) estimate can be obtained from the expression: Sfl= 1-SW. This workflow assumes in principle that resistivity, porosity and saturation are constant within the CSEM resolution.
A common property between the CSEM and seismic data is porosity, which is often used to derive electrical resistivity/seismic velocity relations for shales and reservoir sandstones. A simplistic example that combines Archie’s law with the seismic velocity (Carcione et al. 2007):
where Rf is fluid resistivity, V is seismic derived compressional velocity, Vma is sound velocity of matrix and Vf is velocity of fluid present within the pores of reservoir. This equation, however, handles only one fluid at a time, that could be either water or hydrocarbon/CO2.
One may use different mixtures theories to obtain the electromagnetic and seismic properties, and then combine these theories in different ways. For instance, Archie’s law or the complex refraction-index method CRIM model combined with the time-average equation are two possible choices. Other techniques involve relating the Gassmann equation with the different electromagnetic related equations. Further possibilities involve the HS bounds and the self-similar equation. In the case of plane-layered composites, Backus averaging to relate the conductivity and stiffness tensors can be considered, where the common property is the material proportion (Carcione et al. 2007).
Regarding the patents, a U.S. Patent Application US8064287B2 Published on 22.11.2011 related to a method for mapping a property of a subsurface reservoir includes determining a value of at least one reservoir property from a relevant well and relating at least one property of the reservoir with one seismic attribute and one electromagnetic survey attribute at other geodetic position from the determined relationship. Whereas PCT WO2014000758A1 published on 03.01.2014 related a method for estimating saturation using mCSEM data and stochastic petrophysical models by quantifying the average water saturation in a reservoir given the transverse resistance (TR) obtained from CSEM data. Both the methods, however, used indirect ways to solve for the fluid saturation.
U.S. Patent Application US20090306899A1 published on 10.12.2009 was a Joint processing method of seismic and controlled source electromagnetic (CSEM) surface data. The joint processing was performed by using a common rock physics model which related reservoir properties (such as porosity, lithology, Saturation, and shaliness) to Surface seismic AVO (or AVA) data. The electrical conductivity in the procedure was modeled by using Simandoux equation that uses porosity to relate the electrical conductivity with the seismic output.
U.S. Patent Application US20080059075A1 published on 06.03.2008 documented a joint inversion method for generating Velocity models for pre-stack depth migration (“PSDM'). This method, however, did not demonstrate methods of calculating properties including fluid saturation.
U.S. Patent Application US20090204327A1 published on 13.08.2009 describes method for efficient inversion of controlled-source electro magnetic survey data to obtain a resistivity model of the subsurface of the survey area. The method extracts the dimensions and location of Sub-Surface structures as they may be revealed by existing seismic or other available high resolution survey data from the subsurface area. This method, however, did not include property like fluid saturation computations.
U.S. Patent Application US20140058677A1 published on 27.02.2014 disclosed a method that included performing a first controlled Source electromagnetic Survey at a selected area that includes a reservoir Zone; performing additional controlled source electromagnetic Surveys at the selected area after the first Survey; and inverting measurements from the first Survey and the additional Surveys to identify at least one resistivity change in the reservoir Zone after the first survey, wherein during the inversion, respective measured resistivity values from the first Survey and respective measured resistivity values from the additional Surveys are constrained to be constant, and correspond to one or more areas disposed in the selected area that are outside of the reservoir Zone. This method, however, did not show methods of calculating properties such as fluid saturation.
U.S. Patent Application WO2012173718A1 Published on 20.12.2012 presented a method for estimating subsurface geological properties (including fluid saturation) using multiple type of geophysical data. The inversion process approaches the true model at longer wavelengths first before solving for model parameters expected to vary at short wavelengths. This was achieved by “freezing” various data and model domains of the inversion problem. “Freezing” was defined as fixing, damping, downweighting, or removing particular parts of the objective function pertaining to data or model parameters that might contribute to poor convergence properties during an inversion.
In consideration of the prior art, there had been a need to directly relate acoustic impedance with the resistivity with an ability to calibrate locally, in consideration of the rock matrix and in-situ conditions using bore-hole data.
Brief summary
Therefore, it is a main objective of the present invention to provide a better and innovative method for the estimation of saturation in subsurface rock formations using controlledsource electromagnetic (CSEM) data and acoustic impedance inverted from seismic. The above-mentioned shortcomings associated with the prior art are addressed by way of the following novel improvements.
1) Coming up with a new rock physics model that relates formation resistivity (Rt) with acoustic impedance (AI), by-passing the use of porosity that is typically used to establish the relationship between these properties.
2) Circumvent the use of Gassmann equation to relate with the different electromagnetic constitutive equations. The Gassmann equation is useful; however, it requires the input variables at moduli level instead of directly using the sonic velocities.
3) An essential part of this method is that the model can be calibrated using the nearest well penetrated in the zone of interest. The calibration yields the resistivity of water as manifestation of the background resistivity trend. That saves the effort finding resistivity of water from other petrophysical or laboratory methods.
These upper mentioned benefits are aimed at addressing the deficiencies in the prior art. The improved method is disclosed according to the appended independent claim.
Advantageous further developments are subject of the dependent claims.
A first aspect of the present invention relates to a method for the estimation of fluid saturation in a reservoir comprising the following steps:
a) obtaining interval travel time (Dt), bulk density (RHOB) and deep resistivity data from the nearest well within the zone of interest. Converting the relevant data to acoustic impedance, plotting it onto the AI-Resistivity ratio function plane to obtain the resistivity of water Rw while calibrating the model in terms of the resistivity background.
b) obtaining inverted CSEM survey data from the area of interest,
c) obtaining inverted seismic data in the form of acoustic impedance (AI),
d) calculating the fluid saturation (Sfl) using a novel equation inputting the AI from inverted seismic, resistivity from the inverted CSEM and Rw obtained in step (a).
Brief description of the drawings
Other features and advantages of the invention will be better understood from the following detailed description and the attached drawings in which:
FIG. 1 illustrates typical wireline log data acquisition for subsurface sonic interval time, rock bulk density and resistivity determination;
FIG. 2 shows an example of typical CSEM acquisition in a marine set up in this case;
FIG. 3 is an illustration for seismic data acquisition in a marine set up in this case;
FIG. 4 shows a set of iso-saturation of target fluid curved lines in a three-pole diagram onto AI – Resistivity ratio plane;
FIG. 5 A-B illustrates the plotting of the set of pairs on the same diagram of values of the parameters acquired in a well by three well-logging probes before the Rw calibration (A), and after Rw calibration (B);
FIG. 6 is a resistivity profile in depth plotted against spatial distance, inverted from the CSEM data. The darker the grey shade, higher is the resistivity;
FIG. 7 is an Acoustic impedance (AI) profile inverted from the seismic data. The profile is in depth plotted against spatial distance. The darker the grey shade, higher is AI;
FIG. 8 is the output obtained after using equation 2 showing the Sfl;
FIG. 9 shows the resistivity ratio function computed from CSEM resistivity plotted against the AI obtained from the inverted seismic. The fluid saturation (Sfl) calculated using the present method of invention is represented by grey shade. The darker the grey color, higher is the target fluid saturation;
FIG. 10 is a flowchart showing elementary steps in one embodiment of the present inventive method.
Detailed example
The method of the invention comprises the use of data acquired by CSEM, seismic, calibrated by well-logging tools making it possible to separate the influence of fluids other than in-situ saline water and, thus, to estimate the fluid saturation within sedimentary rocks. Subsurface reservoirs may generally consist of two components: (1) the rock matrix, and (2) the fluid(s) within the pore space (water, oil/gas or CO2).
Data obtained from the wellbore may include so-called “well log” data. Such data are typically recorded and presented against depth in the subsurface of various physical parameters measured by probes lowered into the wellbore. Such probes may include, for example, electrical resistivity, acoustic interval time, bulk density, neutron slowing down length, neutron capture cross-section, natural gamma radiation, and nuclear magnetic resonance relaxation time distribution, among others. The well logging procedure comprises recording of magnitudes of various above mentioned physical properties within a bore-hole using an array of logging probes (FIG. 1, 11), attached with a logging cable (12) connected on the other end to a data recording cabin (13).
The controlled-source electromagnetic (CSEM) methods had been used in hydrocarbon exploration since early in the 20th century. Recent advances in the technique make it possible to remotely measure the total horizontal and vertical electrical resistivity of subsurface formations with considerable accuracy but with moderate vertical resolution. CSEM surveying has become an essential geophysical tool for evaluating the presence of hydrocarbon-bearing reservoirs within the subsurface formations. In this method a controlled electromagnetic transmitter is towed above or positioned between electromagnetic receivers on the seafloor. FIG. 2 illustrates the controlled-source electromagnetic data acquisition method in a body of water above a potential hydrocarbon accumulation (21). The vessel is shown towing an electromagnetic source such as a horizontal electrical dipole (22). Receivers (24) are placed on the seafloor. The source emits a low-frequency current signal that penetrates below the water bottom as indicated in the drawing, A signal path (23) is shown traversing a hydrocarbon-bearing layer (21), which will be characterised by high electrical resistivity, and then being detected by the receivers.
Seismic data acquisition is routinely performed both on land and at sea. At sea, seismic vessels deploy one or more cables (“streamers”) behind the vessel as the vessel moves forward. Each streamer includes multiple receivers in a configuration generally as shown in FIG. 3. Streamer (34) trails behind a vessel (35), which moves forward as the survey progresses. As shown in FIG. 3, source (32) is also towed behind vessel (35). Source (32) and receivers (34) typically deploy below the surface of the ocean. Data is transmitted to the ship (35) through the cables that is recorded and processed. Source (32) emits seismic waves which reflect from boundaries (such as, e.g., formation boundary 31). The reflected waves are detected by receivers (34) and recorded as a function of time by determining the time it takes for seismic waves to propagate from source, reflected at a boundary (31) and back to receivers (34). The recorded signal may yield the information of the position, topography of boundary (31), rock, and in-situ fluid properties. The receivers used in marine seismology are commonly referred to as hydrophones, or marine pressure phones. Inversion of seismic data, depending on the procedure, may yield acoustic impedance, shear impedance, P- wave velocity, S-wave velocity, P- to S- wave ratio, and bulk density.
One embodiment of a method according to the invention will be explained with reference to the flow chart in FIG. 10. The method of the invention makes use, in some embodiments, of data acquired from at least one wellbore (Well A in this case, FIG. 6, 7&8) drilled through subsurface rock formations in an area of interest. The method of the invention contains first of all the Rw calibration of model using three well-logging probes data appropriate for predicting the magnitude of pore fluid. The response of well-logging tools is dependent on the properties related to the components as well as their respective percentage in the rocks investigated. The tool measuring the sonic transit time through the formations is sensitive to the rock porosity and the fluids it contains. We converted the sonic interval time to sonic velocity (115). The probe measuring the density is sensitive to water, other fluids and the void spaces/porosity between the matrix grains. The tool that measures the electric resistivity of the rock makes slight discrimination between the wet clay and the saline water as both are conducting agents, and no discrimination for variations in composition of the matrix if the conducting minerals are not in a continuous phase. The resistivity tool, however, records high resistivity values in case of hydrocarbon, freshwater or CO2 contained in the pore spaces. The product of density with sonic derived velocity is called acoustic impedance. We used acoustic impedance values as a combined augmented response of the sonic and density probes within the method of invention (116). Acoustic impedance is a standard outcome of inversion of seismic data, whereas resistivity (vertical and horizontal) is obtained from CSEM, both the procedures yield independent measurements within a wide areal extent. A function namely resistivity ratio function (
was introduced within the method of invention. The resistivity ratio function was
defined as the square root of the ratio between the resistivity of formation water and the resistivity measured by the resistivity tool (117).
In a salt water-wet porous rocks, the two curves i.e. acoustic impedance and resistivity ratio respond to porosity. But in case of rock pores filled with hydrocarbon, freshwater or CO2 both the acoustic impedance and resistivity measurements respond due to two main effects: 1) the acoustic impedance responds to the presence of low-density low-velocity fluids, and 2) the resistivity ratio measurements respond to the porosity and the resistive fluids (gas/oil, freshwater, CO2). In a rock comprised of 100% matrix content with zero porosity (FIG. 4, 41), or a fluid comprised of 100% of hydrocarbon for instance (43), is assumed to yield infinity resistivity resulting in a zero resistivity ratio value. On the other hand at water pole (42) the resistivity of water (Rw) theoretically becomes equal to the total resistivity (Rt) resulting in resistivity ratio value of 1.
The two properties obtained from the well log data are chosen also so that the collection of pairs of values of acquired parameters (namely the acoustic impedance on the one hand and the resistivity ratio function on the other) at least partly correspond to the equal fluid saturation volume (Sfl) for sedimentary rocks comprising a given proportion of matrix or water are substantially identical.
This selection of petrophysical parameters substantially simplifies the operation for estimating the fluid saturation. In a cross-plot of the two chosen properties, the collection of pairs of values of the said parameters are spread over iso-fluid-saturation curves. A diagram may be drawn where the iso-saturation curved lines converge at the 100% matrix pole (41). A reference curved line (44) representing 0% (or 0 fraction) Sfl which joins the 100% (or 1 fraction) water pole (42) with the 100% (or 1 fraction) matrix pole (41).
The baseline (45) represented by the X-axis against the resistivity ratio function
= 0 was assumed to be having infinity resistivity and zero porosity. If we assume the rock consists of matrix, target fluid (Oil/gas, or CO2 for instance) and water-filled matrix porosity then collection of pairs of values of the parameters serving as reference which is represented by the iso-saturation curved line equivalent to a given fluid percentage within a rock obtained experimentally from values of the two chosen parameters acquired from the data.
This method of determining the Rw to align the 0% (or 0 fraction) Sfl zone data along the 0% (or 0 fraction) fluid reference line implies that, among the zones crossed by the well, some are water-bearing. This is possible if we assume the data pairs with lowest resistivity ratio function values occasionally showing a trend partly parallel to the 0% (or 0 fraction) Sfl reference line (44). It is possible to verify the existence of such zones by comparison with other fluid saturation calculation techniques within a basin. The pairs of values are represented by the set of iso-saturation curved lines, from the line with 0% fluid saturation to the line representing 100% fluid saturation volume within the rock pores. The fluid saturation which corresponds to that is then obtained by applying the following relation:
where VPma, VPfl and VPw are the P-wave velocities of the mineral matrix, target fluid and water respectively, ρma is density of mineral grains, ρfl is density of target fluid, ρw is density of water, Rt is deep resistivity, Rw is the resistivity of water, ‘a’ is tortuosity factor, AI is acoustic impedance and Sfl is the target fluid saturation (in fraction). The tortuosity factor ‘a’ controls the slope of the iso-saturation curved lines and may be selected in a formation zone depending on pore structure, grain size and level of compaction. The relevant constants may be taken from Mavko et al (2009) and vendors’ logging chart books.
From this function (equation 1) we are able to define a set of lines representing different fluid saturations converging at the 100% matrix pole onto the Acoustic impedanceresistivity ratio function plane (FiG. 4 & FIG. 10, step 118).
Rearranging the equation the fluid saturation can be calculated in fraction (that can be converted to a percentage by multiplying with 100) using the following equation:
Until now the Rw is unknown, iterate the value of Rw making the upper right part of the data representing the 100% water-saturated matrix (51 in Figure 5B) to align with the 0% (or 0 fraction) fluid saturation line. The obtained Rw value (FIG. 10, 121) is employed to insert in the step (123).
Bring the inverted CSEM data (FIG. 6 & FIG10, step 112) and inverted seismic data in the form of AI (FIG. 7 & FIG10, step 113) to the same domain (122); time or depth. Putting both the inverted CSEM and AI with the Rw in equation 2 and calculate (123) to obtain the fluid saturation (Sfl)(124). The obtained Sfl profile in this embodiment is shown in FIG. 8, and the computed points from selected data plotted onto an AI vs plane are illustrated in FIG. 9.
The technical solution is only one embodiment of the present invention, to those skilled in the art, the present invention discloses a fundamental principle of the method and applications, straightforward to make various types of modifications or variations, the method is not limited to the specific embodiments of the present invention described above, and therefore the manner described above are only preferred and is not in a limiting sense.
References Cited
PATENT DOCUMENTS US US8064287B2 11/2011 Peter Harris, Lucy Macgregor
W O2014000758A1 01/2014 Torgeir Wiik, Per Atle Olsen, Lars Ole Løseth US 20090306899A1 12/2009 Peter Harris, Joel Walls
US 20080059075A1 03/2008 Daniele Colombo, Michele De Stefano
US 20090204327A1 08/2009 Xinyou Lu, James J. Carazzone
US 20140058677A1 02/2014 Leendert Combee
WO 2012173718A1 12/2012 Christopher DiCaprio, Jan Schmedes, Charlie Jing,
Garrett M. Leahy, Anoop A. Mullur, Rebecca L. Saltzer
OTHER PUBLICATIONS
Archie, G.E. (1942): “The electrical resistivity log as an aid in determining some reservoir characteristics”, Trans. AIME, 146, 01, 54‑62.
Carcione, J.M., B. Ursin & J.I. Nordskag (2007): “Cross-property relations between electrical conductivity and the seismic velocity of rocks”, Geophysics, 72, 5, E193‑E204.
Mavko, G., T. Mukerji & J. Dvorkin (2009): The rock physics handbook: Tools for seismic analysis of porous media, Cambridge university press.
Patent Claims
1. A method for the estimation of fluid saturation in a subsurface reservoir comprising the following steps:
using data provided by inverted CSEM (112), acoustic impedance inverted from seismic (113), and at least one nearest well providing at least three well-logging probes measuring three different parameters (111), selected so that
a) the product of the velocity of sound obtained from one logging-tool (115) with the density data obtained from the second logging-tool, hereby called acoustic impedance (116) develop in the same direction in response to a volumetric change of the water, and target fluid in the said sedimentary rocks,
characterised by
b) the third probe produces measurement signals hereby modified to a resistivity ratio function (117) developing in opposite directions to each other due to the target fluid variation, on the one hand, and the water content, on the other, in the same sedimentary rocks, and
c) the three well-logging probes being further selected so that the resulting pairs within the acoustic impedance-resistivity ratio plane correspond to an equal fluid saturation, associated respectively with the said rocks comprising a given percentage of rock matrix or water, are equal represented by one pair of values of the representative parameters of the 100% fluid saturation, creating a system of sets of pairs of values of the acquired parameters, to obtain a continuous representation of the fluid saturation of the formations penetrated by the well.
d) estimating the resistivity background within the formation of interest (120), simultaneously obtaining the resistivity of water (121) to further use in calculations.
e) obtaining inverted CSEM survey data (112) from a subsurface zone of interest,
f) obtaining inverted seismic data (113) in the form of acoustic impedance,
g) bring the inverted CSEM and acoustic impedance data into same domain (122) either in depth, or time,
h) estimating a fluid saturation Sfl (124) using an equation by inputting the said data (123), whereby Sfl = 1-Sw.
2. The method of claim 1, wherein the measurements made by at least three well probes are employed, adapted for measuring the electric resistivity of the formation penetrated, the transit time of sound through the same ground, and the density of the said ground.
3. The method of claim 2, wherein the measurements made by the acoustic tool are converted to sound velocity (115), the product of the sound velocity values with the density readings obtained by the density tool is used, calling which as acoustic impedance (116) values.
4. The method as claimed in claim 2, a resistivity ratio function is defined as the square root of the ratio between the resistivity of water and the resistivity values obtained from the resistivity probe (117).
5. The method of claim 2, wherein measurements made by a well probe measuring the electric resistivity of the zone in the sub-surface and two other well probes measuring the transit time of sound and the density through this same zone, a representation diagram is chosen as a function of the resistivity ratio function and of the acoustic impedance where said system of sets of pairs of values of the parameters acquired, each associated with the same saturation, may be likened to a set of parallel iso-fluid saturation curves, the fluid saturation associated with each pair of values of the acoustic impedance and of the resistivity ratio measured in the well then being determined by identifying the saturation curve passing through the point representative of said pair in the chosen representation diagram (118).
6. The method of claim 2, wherein the slope of iso-volumetric content curves is controlled by the tortuosity factor ‘a’ that is selected for a formation zone considering the pore structure, grain size and level of compaction.
7. The method of claim 2, wherein the resistivity of water (121) is determined by iterating the resistivity of water while aligning the 100% water-saturated borehole data onto the acoustic impedance – resistivity ratio plane with the 0% fluid saturation reference curved line (120).
8. The method of claim 1, wherein the reference set is established by selecting, from all the pairs of values acquired from the inverted CSEM data and AI data, at least one specific pair of quantities for which a given fluid saturation in fraction or equivalent percentage may be associated.
9. The method of claim 1, wherein quantities from each pair of the parameters acquired in the CSEM and AI is demonstrated in a diagram as a function of coordinates, one measuring acoustic impedance in the rock and the other the square root of the ratio between the resistivity of water and the resistivity of rock, hereby called the resistivity ratio function, where the collection of pairs of values equivalent to a corresponding content are manifested by a system of curved lines parallel to a reference curved line representing a zero fluid saturation in fraction or equivalent percentage, to which a given fluid saturation may be allocated, the position of the latter being ascertained by at least two representative points, one being associated with a rock which contains only the matrix and said given fluid saturation, the other with a pair of values acquired by the input data with which this same fluid saturation may be associated.
10. The method of claim 9, wherein the positions of the iso-fluid saturation curved lines are determined between an axis with the 100% rock matrix member on one end and the 100% fluid saturation on the other end, both represented by the values taken by the two parameters.
11. The method of claim 1, wherein the pairs of values typical of the target fluids and of the matrix are obtained from the existing literature.
12. The method of claim 1, wherein using an organic-rich shale data the increase in values of fluid saturation may indicate increase in maturation.
Claims (12)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| NO20191431A NO346380B1 (en) | 2019-12-05 | 2019-12-05 | Fluid identification and saturation estimation using CSEM and seismic data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| NO20191431A NO346380B1 (en) | 2019-12-05 | 2019-12-05 | Fluid identification and saturation estimation using CSEM and seismic data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| NO20191431A1 NO20191431A1 (en) | 2021-06-07 |
| NO346380B1 true NO346380B1 (en) | 2022-07-04 |
Family
ID=77515137
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| NO20191431A NO346380B1 (en) | 2019-12-05 | 2019-12-05 | Fluid identification and saturation estimation using CSEM and seismic data |
Country Status (1)
| Country | Link |
|---|---|
| NO (1) | NO346380B1 (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11914091B2 (en) * | 2021-01-23 | 2024-02-27 | Manzar Fawad | Rock physics model for fluid identification and saturation estimation in subsurface reservoirs |
| NO346572B1 (en) * | 2021-01-23 | 2022-10-17 | Univ Oslo | Rock physics model for fluid identification and saturation estimation in subsurface reservoirs |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080059075A1 (en) * | 2006-09-04 | 2008-03-06 | Daniele Colombo | Methods and apparatus for geophysical exploration via joint inversion |
| US20090204327A1 (en) * | 2006-07-25 | 2009-08-13 | Xinyou Lu | Method For Determining Physical Properties of Structures |
| US20090306899A1 (en) * | 2008-06-06 | 2009-12-10 | Ohm Limited | Geophysical surveying |
| WO2012173718A1 (en) * | 2011-06-17 | 2012-12-20 | Exxonmobil Upstream Research Company | Domain freezing in joint inversion |
| US20140058677A1 (en) * | 2012-08-23 | 2014-02-27 | Westerngeco, L.L.C. | Method for processing electromagnetic data |
-
2019
- 2019-12-05 NO NO20191431A patent/NO346380B1/en not_active Application Discontinuation
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090204327A1 (en) * | 2006-07-25 | 2009-08-13 | Xinyou Lu | Method For Determining Physical Properties of Structures |
| US20080059075A1 (en) * | 2006-09-04 | 2008-03-06 | Daniele Colombo | Methods and apparatus for geophysical exploration via joint inversion |
| US20090306899A1 (en) * | 2008-06-06 | 2009-12-10 | Ohm Limited | Geophysical surveying |
| WO2012173718A1 (en) * | 2011-06-17 | 2012-12-20 | Exxonmobil Upstream Research Company | Domain freezing in joint inversion |
| US20140058677A1 (en) * | 2012-08-23 | 2014-02-27 | Westerngeco, L.L.C. | Method for processing electromagnetic data |
Also Published As
| Publication number | Publication date |
|---|---|
| NO20191431A1 (en) | 2021-06-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8729903B2 (en) | Method for remote identification and characterization of hydrocarbon source rocks using seismic and electromagnetic geophysical data | |
| Castagna et al. | Principles of AVO crossplotting | |
| US8700372B2 (en) | Method for 3-D gravity forward modeling and inversion in the wavenumber domain | |
| CA2649370C (en) | Integrated earth formation evaluation method using controlled source electromagnetic survey data and seismic data | |
| US8064287B2 (en) | Method for interpreting seismic data and controlled source electromagnetic data to estimate subsurface reservoir properties | |
| US7912649B2 (en) | Geophysical surveying | |
| US11725510B2 (en) | Fluid identification and saturation estimation using CSEM and seismic data | |
| US20220236439A1 (en) | Rock physics model for shale volume estimation in subsurface reservoirs | |
| Foti et al. | Experiments of joint acquisition of seismic refraction and surface wave data | |
| US20080162050A1 (en) | Method for interpreting seismic data and controlled source electromagnetic data to estimate subsurface reservoir properties | |
| Mondol | Well logging: Principles, applications and uncertainties | |
| US11914091B2 (en) | Rock physics model for fluid identification and saturation estimation in subsurface reservoirs | |
| Abdideh et al. | Cluster analysis of petrophysical and geological parameters for separating the electrofacies of a gas carbonate reservoir sequence | |
| Carcione et al. | The seismic response to overpressure: a modelling study based on laboratory, well and seismic data | |
| Wagner et al. | Quantitative application of poststack acoustic impedance inversion to subsalt reservoir development | |
| NO346380B1 (en) | Fluid identification and saturation estimation using CSEM and seismic data | |
| Ezersky et al. | Quantitative assessment of in-situ salt karstification using shear wave velocity, Dead Sea | |
| Riedel et al. | Gas hydrate concentration estimates from chlorinity, electrical resistivity and seismic velocity | |
| Niculescu et al. | Formation evaluation challenges in Pliocene gas-bearing reservoirs from the Romanian Western Black Sea shelf | |
| NO346488B1 (en) | Rock physics model for shale volume estimation in subsurface reservoirs | |
| Riedel et al. | Gas hydrate offshore Vancouver Island, northern Cascadia margin | |
| Wang et al. | Deep carbonate reservoir and gas prediction based on multicomponent seismic amplitude attributes—A case study | |
| OPAWANDE | HYDROCARBON CHARACTERIZATION AND PROSPECT IDENTIFICATION OF YZ FIELD, NIGER DELTA | |
| Riofrio et al. | High-Definition-Mapping UDAR Inversion Provides Accurate Geobody Geometries in a Complex 3D Reservoir | |
| Watkins et al. | A Geology-Based, Non-Seismic Attribute Method to Generate Facies, Lithology, and Petrophysical Parameters in the Chinook and Cascade Fields, Walker Ridge, Gulf of Mexico, USA |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| FC2A | Withdrawal, rejection or dismissal of laid open patent application |