WO2011077271A1

WO2011077271A1 - Methods and apparatus for characterization of a petroleum reservoir employing compositional analysis of fluid samples and rock core extract

Info

Publication number: WO2011077271A1
Application number: PCT/IB2010/055156
Authority: WO
Inventors: Andrew E. Pomerantz; Ballard Andrews; Eric Lehne; Oliver C. Mullins
Original assignee: Schlumberger Canada Limited; Services Petroliers Schlumberger; Schlumberger Holdings Limited; Schlumberger Technology B.V.; Prad Research And Development Limited
Priority date: 2009-12-21
Filing date: 2010-11-12
Publication date: 2011-06-30

Abstract

A methodolgy for reservoir characterization involves downhole fluid sampling within a wellbore to collect a hydrocarbon fluid sample, and core sampling operations to collect a core sample at a location identified as a potential flow barrier in the reservoir. Laboratory analysis analyzes the compositions of the hydrocarbon fluid sample and fluids extracted from the core sample. The compositions are compared to characterize properties of the reservoir. The compositional properties of the core sample extract are compared to those of the incompatible fluid-insoluble fraction of the hydrocarbon fluid sample. If there are similarities between the compositional properties, it is inferred that bitumen of the core sample formed by a late incompatible fluid charge. If there are differences between the compositional properties and biomarkers indicative of high levels of biodegradation are present in the core fluid extract, it is inferred that bitumen of the core sample formed by biodegradation.

Description

METHODS AND APPARATUS FOR CHARACTERIZATION OF A PETROLEUM RESERVOIR EMPLOYING COMPOSITIONAL ANALYSIS OF FLUID SAMPLES AND

ROCK CORE EXTRACT

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001 ] The present invention claims priority from US Provisional Patent Application 61/288,415, filed on December 21, 2009, incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

Field of the Invention

[0002] The present invention relates to methods and apparatus for characterizing petroleum fluids extracted from a hydrocarbon-bearing geological formation. The invention has application to reservoir architecture understanding, although it is not limited thereto.

Description of Related Art

[0003] Petroleum consists of a complex mixture of hydrocarbons of various molecular weights, plus other organic compounds. The exact molecular composition of petroleum varies widely from formation to formation. The proportion of hydrocarbons in the mixture is highly variable and ranges from as much as 97 percent by weight in the lighter oils to as little as 50 percent in the heavier oils and bitumens. The hydrocarbons in petroleum are mostly alkanes (linear or branched), cycloalkanes, aromatic hydrocarbons, or more complicated chemicals like asphaltenes. The other organic compounds in petroleum typically contain carbon dioxide (C0₂), nitrogen, oxygen, and sulfur, and trace amounts of metals such as iron, nickel, copper, and vanadium.

[0004] Petroleum is usually characterized by SARA fractionation where asphaltenes are removed by precipitation with a paraffinic solvent and the deasphalted oil is separated into saturates, aromatics, and resins by chromatographic separation.

[0005] The saturates include alkanes and cycloalkanes. The alkanes, also known as paraffins, are saturated hydrocarbons with straight or branched chains which contain only carbon and hydrogen and have the general formula C_nH2_n+2- They generally have from 5 to 40 carbon atoms per molecule, although trace amounts of shorter or longer molecules may be present in the mixture. The alkanes include methane (CH₄), ethane (C₂H₆), propane (C₃H₈), i-butane (iC₄Hio), n-butane (nC₄Hio), i-pentane (iCsH^), n-pentane (nCsH^), hexane (C₆H₁₄), heptane (C₇H₁₆), octane (C₈H₁₈), nonane (C9H2₀), decane (C₁₀H₂₂), hendecane (C11H24) - also referred to as endecane or undecane, dodecane (C₁₂H₂₆), tridecane (C₁₃H₂8), tetradecane (C₁₄H₃o), pentadecane (C15H₃2) and hexadecane (C₁₆H₃₄). The cycloalkanes, also known as napthenes, are saturated hydrocarbons which have one or more carbon rings to which hydrogen atoms are attached according to the formula C_nH2_n- Cycloalkanes have similar properties to alkanes but have higher boiling points. The cycloalkanes include cyclopropane (C₃H₆), cyclobutane (C₄H₈),

cyclopentane (C5H1₀), cyclohexane (C₆H₁₂), and cycloheptane (C₇H₁₄).

[0006] The aromatic hydrocarbons are unsaturated hydrocarbons which have one or more planar six-carbon rings called benzene rings, to which hydrogen atoms are attached with the formula C_nH_n. They tend to burn with a sooty flame, and many have a sweet aroma. The aromatic hydrocarbons include benzene (C₆H6) and derivatives of benzene, as well as poly aromatic hydrocarbons. [0007] Resins are the most polar and aromatic species present in the deasphalted oil and, it has been suggested, contribute to the enhanced solubility of asphaltenes in crude oil by solvating the polar and aromatic portions of the asphaltenic molecules and aggregates.

[0008] Asphaltenes are insoluble in n-alkanes (such as n-pentane or n-heptane) and soluble in toluene. The C:H ratio is approximately 1:1.2, depending on the asphaltene source. Unlike most hydrocarbon constituents, asphaltenes typically contain a few percent of other atoms (called heteroatoms), such as sulfur, nitrogen, oxygen, vanadium, and nickel. Heavy oils and tar sands contain much higher proportions of asphaltenes than do medium- API oils or light oils.

Condensates are virtually devoid of asphaltenes. As far as asphaltene structure is concerned, experts agree that some of the carbon and hydrogen atoms are bound in ring-like, aromatic groups, which also contain the heteroatoms. Alkane chains and cyclic alkanes contain the rest of the carbon and hydrogen atoms and are linked to the ring groups. Within this framework, asphaltenes exhibit a range of molecular weight and composition. Asphaltenes have been shown to have a distribution of molecular weight in the range of 300 to 1400 g/mol with an average of about 750 g/mol. This is compatible with a molecule contained seven or eight fused aromatic rings, and the range accommodates molecules with four to ten rings. It is also known that asphaltene molecules aggregate to form nanoaggregates and clusters.

[0009] Non-movable bitumen (for example, pyrobitumen, migrabitumen, gilsonite, and tar) occurs in carbonate and siliciclastic oil and gas reservoirs in many basins throughout the world.

Such non-movable bitumen includes a high fraction of asphaltenes and can be formed from petroleum in the reservoir through natural or artificial alteration processes such as thermal cracking of oil (pyrobitumen), gas deasphalting of oil (asphaltene precipitation), or by inspissation, water washing, or oxidation (tar). Non-movable bitumen acts as a flow barrier to hydrocarbons and thus can contribute to compartmentalization of the reservoir fluids. Reservoir compartmentalization can significantly hinder production of fluids from the reservoir and can make the difference between an economically viable field and an economically nonviable field. The impact of the non-movable bitumen on production depends upon the type of the non- movable bitumen, the solubility of the non-movable bitumen, the mechanism of formation of the non-movable bitumen, and the volume and distribution of the non-movable bitumen in the reservoir.

[0010] Techniques that aid an operator in accurately describing reservoir compartments and their distribution can increase understanding of such reservoirs and ultimately raise production. Conventionally, reservoir architecture has been determined utilizing pressure-depth plots and pressure gradient analysis with traditional straight-line regression schemes. This process may, however, be misleading as fluid compositional changes and compartmentalization give distortions in the pressure gradients, which result in erroneous interpretations of fluid contacts or pressure seals. Additionally, pressure communication does not prove flow connectivity.

[0011 ] Non-movable tar deposits, which are commonly referred to as tar mats, are present in many oil reservoirs throughout the world and they are quite common in carbonate reservoirs in the Middle East. Tar mats are usually - but not always - located at or near present-day oil/water contacts. In these reservoirs, it is common to inject water at or near the tar mat in order to maintain reservoir pressure during production. In these scenarios, understanding the mechanism of formation of the non-movable tar mat as well as the volume and distribution of the non- movable tar mat in the reservoir can aid in optimizing the desired effect of the water injection while minimizing the loss of oil that can result from such processes. BRIEF SUMMARY OF THE INVENTION

[0012] It is therefore an object of the invention to provide methods and apparatus that accurately characterize compositional components and fluid properties at varying locations in a reservoir in order to allow for accurate reservoir analysis, particularly for any non-movable bitumen deposit (e.g., tar mat) that may exist in the reservoir.

[0013] In accord with the objects of the invention, a method is provided for characterizing a hydrocarbon reservoir of interest traversed by a wellbore. The method includes performing downhole fluid sampling operations at a location within the wellbore to collect a hydrocarbon fluid sample at the location, and performing core sampling operations to collect at least one core sample at a location identified as a potential low permeability flow barrier. The hydrocarbon fluid samples and core sample(s) are transported to a laboratory. In the laboratory, laboratory analysis is performed that analyzes the composition of the hydrocarbon fluid sample. Laboratory operations are performed that extract core fluid from the core sample and analyze the compositions of the extracted fluid. The compositions of the hydrocarbon fluid sample and the extracted core fluid are compared to one another in order to characterize properties of the reservoir of interest.

[0014] In one embodiment, chain-of-custody of the hydrocarbon fluid sample is validated before carrying out the laboratory analysis thereon. Such chain-of-custody analysis relies on downhole fluid analysis performed on live hydrocarbon fluids corresponding to the collected hydrocarbon fluid sample, as well as laboratory fluid analysis on the hydrocarbon fluid sample that reconstructs the downhole fluid analysis.

[0015] In an exemplary embodiment, the compositional properties of the core sample extract are compared to those of the incompatible fluid-insoluble fraction of the collected hydrocarbon fluid sample in the event that the core sample contains bitumen. An incompatible fluid being defined as any fluid that poorly dissolves asphaltenes and other heavy ends of petroleum such that addition of the fluid to oil results in some asphaltenes or other heavy ends falling out of solution. Examples of incompatible fluids include gas, carbon dioxide, and very light oils (i.e. condensates). If there are similarities between the compositional properties of the core sample extract compared to those of the incompatible fluid-insoluble fraction of the collected hydrocarbon fluid sample, it is inferred that it is likely that the bitumen of the core sample formed by a late incompatible fluid charge. If there are differences between the compositional properties of the core sample extract compared to those of the incompatible fluid-insoluble fraction of the collected hydrocarbon sample, and biomarkers indicating extensive

biodegradation are present in the core fluid extract, it is inferred that it is likely that the bitumen of the core sample formed by biodegradation.

[0016] In one embodiment, downhole fluid analysis over a number of locations in the wellbore is used to predict compositional gradients within the wellbore. The results of such downhole fluid analysis and/or the compositional gradients based thereon are used to identify the location of a potential flow barrier in the wellbore. Downhole fluid sampling operations (if not done already) and downhole core sampling are then carried out at or near the location of the potential flow barrier.

[0017] Additional objects and advantages of the invention will become apparent to those skilled in the art upon reference to the detailed description taken in conjunction with the provided figures. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] FIG. 1 is a schematic diagram of an exemplary workflow for petroleum reservoir analysis according to the present invention.

[0019] FIG. 2A is a schematic diagram of an exemplary petroleum reservoir fluid analysis tool that can be used as part of the methodology of the present invention.

[0020] FIG. 2B is a schematic diagram of an exemplary fluid analysis module suitable for use in the tool of FIG. 2A.

[0021 ] FIGS. 3A - 3B, collectively, are a flow chart of exemplary data analysis operations that are part of the workflow of FIG. 1 in accordance with the present invention.

[0022] FIG. 4 is a flow chart of preferred data analysis operations for inferring reservoir structure as part of the operations of FIGS. 3 A and 3B.

DETAILED DESCRIPTION OF THE INVENTION

[0023] FIG. 1 illustrates an exemplary workflow for petroleum reservoir analysis according to the present invention. In stage 10, a downhole fluid sampling tool is deployed within a wellbore traversing a reservoir of interest and operated to extract and store one or more live oil samples within the tool. In stage 12, a downhole fluid analysis tool, which can be the same tool used for downhole fluid sampling or a separate tool, is deployed within the wellbore traversing the reservoir of interest and operated to extract live oil fluid from the formation adjacent the wellbore and perform downhole fluid analysis (DFA) of the live oil fluid. The downhole fluid analysis derives properties (e.g., gas-oil ratio (GOR), oil-based mud contamination, saturation pressure, live fluid density, live fluid viscosity, and compositional component concentrations) that characterize the live oil fluid at the pressure and temperature of the formation. The fluid properties measured by downhole fluid analysis in stage 12 together with other sample data (e.g., sample number, date of acquisition, depth, and tool configuration data) are stored as DFA data in data store 14. In the preferred embodiment, the data store 14 is realized as a central unitary database that contains sampling logs, transfer and shipping information, and all downhole, wellsite, field, and laboratory measurements. Such a unitary design provides several functions including management of access and reporting, as well as data transfer to modeling and analysis applications (stages 26, 28, 30). Alternately, the data store 14 can be realized by a plutrality of database systems where data of interest is transferred between databases by electronic communication or other means.

[0024] In stage 16, a coring tool is deployed within the wellbore traversing the reservoir of interest and operated to extract one or more core samples from the formation. There are several types of core samples that can be recovered from the wellbore, including full-diameter whole cores, oriented cores, native state cores and sidewall cores. In the one embodiment whole cores are extracted while drilling the wellbore. In another embodiment the coring tool obtains one or more sidewall cores from the formation adjacent the wellbore. An example of a commercially available coring tool of this type is the Mechanical Sidewall Coring Tool (MSCT) available from Schlumberger Technology Corporation of Sugar Land, Texas, USA. The MSCT employs a hollow coring bit that is deployed in a configuration where it extends generally transverse to the borehole axis. The hollow coring bit is mechanically rotated relative to the tool housing. The coring bit may be extended into the formation as the bit rotates, thereby capturing a sidewall core within the hollow interior of the coring bit. The MSCT is further described in US Patents 4,714,119 and 5,667,025. Another example of a commercially available sidewall coring tool is the Chronological Sample Taker (CST), also available from Schlumberger Technology

Corporation. The CST employs explosive charges to fire hollow cylindrical bullets into the formation at desired sample depths. US Patents 2,928,658; 2,937,005; 2,976,940; 3,003,569; 3,043,379; 3,080,005; and 4,280,568 disclose various types and aspects of explosive-type sidewall coring tools. The coring tool can be run in combination with a gamma ray tool (or other suitable logging tool) to correlate with openhole logs for accurate, real-time depth control of the coring points. Each core sample is isolated and identified from other core samples. Both the live oil sample collected in stage 10 and the core sample collected in stage 16 are assigned sample numbers and validated at the wellsite and transported to a laboratory for analysis.

[0025] In stage 18, the downhole fluid analysis measurements are optionally reproduced in the laboratory for chain-of-custody analysis. More specifically, the live oil sample is reconditioned to the formation reservoir pressure at the sample depth (as dictated by the DFA data stored in the data store 14). The reconditioned live oil sample is then subjected to analytical measurements (e.g., GOR, oil -based mud contamination, fluid composition) that replicate the downhole fluid analysis measurements, and the results of the laboratory measurements are compared to the results of the corresponding downhole measurements stored as part of the DFA data in data store 14. If there is agreement between the downhole and laboratory fluid measurements, the chain-of-custody is verified. If there is disagreement between the downhole and laboratory fluid measurements, the chain-of-custody verification fails and the sample and the laboratory measurements based thereon can be discarded or otherwise ignored. In the case of failure, actions can be taken to identify and correct the cause of the failure, which can arise from hardware failure of the downhole fluid analysis tool or laboratory tool, and inappropriate sampling, sample reconditioning, and/or sample transfer techniques.

[0026] In stage 20, the core sample is analyzed in the laboratory and the results of the analysis are stored in the data store 14. Such analysis can include bulk measurements (e.g., porosity, grain density, permeability, and residual saturation) to measure properties of the core sample. In the case that the core sample includes movable hydrocarbons, hydrocarbon fluid can be extracted from the core sample by centrifuging the core sample. In the case that the core sample is non-movable bitumen, hydrocarbon fluid can be extracted from the bitumen core sample using a solvent. In either case, the composition of the extracted hydrocarbon fluid can be analyzed by geochemical analysis, which can be carried out by a variety of techniques including:

Gas chromatography, including gas chromatography with various detection schemes (flame ionization detector, thermal conductivity detector, mass spectrometer);

Saturates-aromatics-resins-asphaltenes (SARA) analysis;

Optical spectroscopy in the ultraviolet, visible, and near-infrared regions;

Infrared spectroscopy (including instruments using Fourier transform);

Fluorescence spectroscopy;

Raman spectroscopy;

Liquid chromatography, including various modifications (high pressure/performance, reverse phase, with mass spectrometric detection);

Pyrolysis experiments with gas chromatography or other detection methods; Isotope analysis (for example, performed using an isotope ratio mass spectrometer); and

Nuclear magnetic resonance (NMR) spectroscopy using various nuclei ( 13 C, 1 H, for example).

[0027] In the preferred embodiment, SARA analysis and/or NMR spectroscopy can also be carried out in the labarotary as part of stage 20. Such analysis is effective in characterizing the incompatible fluid-insoluble fractions (including the high molecular weight components including resins and asphaltenes) that can be part of the extracted hydrocarbons.

[0028] The analysis of stage 20 can also employ high resolution compositional analysis of the core extract. Examples of such high resolution compositional anlayses include: two-dimensional gas chromatography (GCxGC), including various detection schemes (flame ionization detector, thermal conductivity detector, mass spectrometer, for example) - this technique separates components of the sample along two dimensions (rather than just one as in traditional gas chromatography), greatly enhancing the resolution;

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), including the use of various ionization techniques (such as electrospray ionization, atmospheric pressure chemical ionization, atmospheric pressure photoionization, and others - this technique measures the molecular weight of different components of crude oil to sufficient accuracy and precision that their elemental compositions can be determined;

X-ray absorption near edge spectroscopy (XANES), including carbon, nitrogen, and

(especially) sulfur elements - this technique measures the local chemical environment around the measured element (for example, sulfur XANES measurements can determine the distribution of oxidation states of sulfur in petroleum); and

X-ray Raman spectroscopy on carbon (XRS). This technique measures the way in which fused aromatic rings are connected.

From these high resolution measurements, more detailed information on the chemical composition of the petroleum of the core extract can be determined, enabling more confident reservoir characterization.

[0029] In stage 20, live oil sample(s) whose chain- of-custody has been verified can be subjected to geochemical and high resolution compositional analysis similar to that described above for the core extract). From these geochemical and high resolution measurements, more detailed information on the chemical composition of the petroleum of the live oil sample(s) can be determined, enabling more confident reservoir characterization. Moreover, other laboratory compositional and property analysis can be performed on the live oil sample as desired.

[0030] In stage 22, other downhole analyses can be performed within one or more wellbores that traverse the reservoir of interest. Such analyses can include petrophysical measurements (such as resistivity, neutron logs, density, sonic, borehole seismic, and NMR) and geologic measurements. The results of such analyses are stored in the data store 14.

[0031 ] In stage 24, three-dimensional (and four-dimensional) subsurface seismic analysis of the reservoir of interest can be performed to collect seismic data that can be used to characterize the structure of the rock formations of the reservoir as well as characterize reservoir flow properties such as fracture density, porosity, and permeability distribution. The seismic data collected in stage 24 is stored in the data store 14.

[0032] In stage 26, the data that characterizes the compositions and other fluid properties of the reservoir fluids as derived from the downhole fluid analysis of stage 12 can be processed to model the compositions and thermodynamic pressure-volume-temperature (PVT) properties of the reservoir as a function of depth within the reservoir. Such analysis can be performed in realtime in conjunction with the downhole fluid analysis of stage 12 in order to provide guidance as to the accuracy and effectiveness of the downhole fluid analysis and make a decision as to whether additional downhole fluid analysis is necessary. Furthermore, the data characterizing the composition and fluid properties of the reservoir fluids stored in data store 14 (which is derived from the downhole fluid analysis of stage 12 and the laboratory analysis of stage 20 and possibly other analysis) can be processed off-line to model the compositions and thermodynamic (PVT) properties of the reservoir as a function of depth within the reservoir. The processing and analysis of stage 26 can predict incipient gas and liquid hydrate formation conditions in reservoir fluids and/or the thermodynamic precipitation point of waxes and asphaltenes with knowledge of reservoir fluid compositions. Module accuracy can be confirmed by laboratory testing. In an exemplary embodiment, PVTpro software, together with the dbrSOLIDS and dbrHydrate softwares available from Schlumberger Canada Limited of Edmonton, Alberta, Canada, is used to carry out the compositional and thermodynamic modeling of stage 26. The compositional and thermodynamic model data generated in stage 26 is stored in data store 14.

[0033] In stage 28, the seismic data stored in the data store 14 (which is derived from the seismic analysis of stage 24) as well as the results of the petrophysical and geologic

measurements of stage 22 as stored in the data store 14 can be processed to model, visualize, and analyze the geological structures of the reservoir of interest. Such modeling can involve surface mapping, siesmic mapping and analysis, as well as borehole geology mapping and analysis as is well known in the arts. In an exemplary embodiment, GeoFrame, Geo Viz, and Petrel softwares available from Schlumberger Technology Corporation are used to carry out the reservoir modeling, visualization, and analysis of stage 28. The geological model data generated in stage 28 is stored in data store 14.

[0034] In stage 30, the geological model data stored in the data store 14 in stage 28 and/or the compositional and thermodynamic model data stored in the data store 14 in stage 26 can be used for analysis and management of the reservoir of interest.

[0035] For example, geological model data stored in the data store 14 in stage 28 and/or the compositional and thermodynamic model data stored in the data store 14 in stage 26 can be input to basin modelling software that models and visualizes the geological structures of the reservoir along with a record of the generation, migration, accumulation, and loss of oil and gas in the reservoir of interest over time. For example, the PetroMod software available from

Schlumberger Technology Corporation can be used for basin modelling as part of stage 30.

[0036] In another example, the geological model data stored in the data store 14 in stage 28 and/or the compositional and thermodynamic model data stored in the data store 14 in stage 26 can be used for planning and optimizing production from the reservoir of interest. Such data can be used to evaluate different production scenarios in order to optimize production efficiency and recovery. Moreover, the data can be input to reservoir simulators that provide for modelling and visualization of production scenarios to assist in production decision-making and optimization over time. For example, Eclipse software available from Schlumberger Technology Corporation can be used for reservoir simulation as part of stage 30. [0037] In stage 30, preferably as part of basin modelling, the compositions of a non-movable bitumen core sample extract as stored in the data store 14 in stage 20 are compared to the compositions (particularly the incompatible fluid-insoluble fractions and possibly other fractions) of the live oil sample as stored in the data store 14 in stages 12, 18, and/or 20 to infer structure (or other properties) of the reservoir of interest.

[0038] For example, if the compositional properties (chemical fingerprint) of the bitumen core sample extract is similar to the chemical fingerprint of the incompatible fluid-insoluble fraction of the live oil sample(s) (or that of the formation fluid measured by DFA) at or near the depth of the bitumen core sample from which the extract was produced, it can be inferred that the non-movable bitumen layer of the reservoir was likely formed by a late incompatible fluid charge. In this case, the non-movable bitumen layer is located in the portions of the reservoir that are below those portions exposed to the incompatible fluid charge. Such locations (or hints at these locations) can be depicted visually as part of the basin model or added thereto for visualization purposes. If the chemical fingerprint of the bitumen core sample extract is dissimilar to the chemical fingerprint of the incompatible fluid-insoluble fraction of the live oil sample(s) (or that of the formation fluid measured by DFA) at or near the depth of the bitumen core sample from which the extract was produced and the laboratory compositional analysis shows the presence of biomarkers indicative of biodegradation, it can be inferred that the non- movable bitumen layer of the reservoir was likely formed by biodegradation. In this case, the non-movable bitumen layer is located in the portions of the reservoir at a current or past water- oil contact and thus conductive to biodegradation. Such locations (or hints at these locations) can be depicted visually as part of the basin model or added thereto for visualization purposes. Examples of biomarkers indicative of biodegradation in the core extract include 25-norphases, hopanes, steranes and organic acids with low acyclic: cyclic ratios. The presence of such biomarkers can be measured in the laboratory in stage 20 by gas chromatography with various columns (packed column, capillary columns) and detectors (flame-ionization detector, thermal conductivity detector, mass spectrometer) and by high resolution mass spectrometry.

[0039] FIG. 2A illustrates an exemplary borehole sampling and analysis tool 100 suspended in the borehole 112 from the lower end of a typical multiconductor cable 115 that is spooled in a usual fashion on a suitable winch on the formation surface. The cable 115 is electrically coupled to an electrical control system 18 on the formation surface. The tool 100 includes an elongated body 119 which carries a selectively extendable fluid admitting assembly 120 and a selectively extendable tool anchoring member 121 which are respectively arranged on opposite sides of the tool body. The fluid admitting assembly 120 is equipped for selectively sealing off or isolating selected portions of the wall of the borehole 112 such that fluid communication with the adjacent earth formation 114 is established. The fluid admitting assembly 120 and tool 100 include a flowline leading to a fluid analysis module 125. The formation fluid obtained by the fluid admitting assembly 120 flows through the flowline and through the fluid analysis module 125. The fluid may thereafter be expelled through a port or it may be sent to one or more fluid collecting chambers 122 and 123 which may receive and retain the fluids obtained from the formation. With the fluid admitting assembly 120 sealingly engaging the formation 114, a short rapid pressure drop can be used to break the mudcake seal. Normally, the first fluid drawn into the tool will be highly contaminated with mud filtrate. As the tool continues to draw fluid from the formation 114, the area near the assembly 120 cleans up and reservoir fluid becomes the dominant constituent. The time required for cleanup depends upon many parameters, including formation permeability, fluid viscosity, the pressure difference between the borehole and the formation, and overbalanced pressure difference and its duration during drilling. Increasing the pump rate can shorten the cleanup time, but the rate must be controlled carefully to preserve formation pressure conditions.

[0040] The fluid analysis module 125 includes means for measuring the temperature and pressure of the fluid in the flowline. The fluid analysis module 125 derives properties that characterize the formation fluid sample at the flowline pressure and temperature. In the preferred embodiment, the fluid analysis module 125 measures absorption spectra and translates such measurements into concentrations of several alkane components and groups in the fluid sample. In an illustrative embodiment, the fluid analysis module 125 provides measurements of the concentrations (e.g., weight percentages) of carbon dioxide (C0₂), methane (CH₄), ethane (C₂H₆), the C3-C5 alkane group, the lump of hexane and heavier alkane components (C6+), and asphaltene content. The C3-C5 alkane group includes propane, butane, and pentane. The C6+ alkane group includes hexane (C₆H₁₄), heptane (C₇H₁₆), octane (CsH^), nonane (C9H2₀), decane (C1₀H22), hendecane (CnH₂₄) - also referred to as endecane or undecane, dodecane (C₁₂H₂₆), tridecane (C₁₃H₂8), tetradecane (C₁₄H₃o), pentadecane (C₁₅H₃₂), hexadecane (C₁₆H₃₄), etc. The fluid analysis module 125 also provides a means that measures live fluid density (p) at the flowline temperature and pressure, live fluid viscosity (μ) at flowline temperature and pressure (in cp), formation pressure, and formation temperature.

[0041 ] Control of the fluid admitting assembly 120 and fluid analysis module 125, and the flow path to the collecting chambers 122, 123 is maintained by the control system 118. As will be appreciated by those skilled in the art, the fluid analysis module 125 and the surface-located electrical control system 118 include data processing functionality (e.g., one or more microprocessors, associated memory, and other hardware and/or software) to implement the invention as described herein. The electrical control system 118 can also be realized by a distributed data processing system wherein data measured by the tool 100 is communicated (preferably in real-time) over a communication link (typically a satellite link) to a remote location for data analysis as described herein. The data analysis can be carried out on a workstation or other suitable data processing system (such as a computer cluster or computing grid).

[0042] Formation fluids sampled by the tool 100 may be contaminated with mud filtrate. That is, the formation fluids may be contaminated with the filtrate of a drilling fluid that seeps into the formation 114 during the drilling process. Thus, when fluids are withdrawn from the formation 114 by the fluid admitting assembly 120, they may include mud filtrate. In some examples, formation fluids are withdrawn from the formation 114 and pumped into the borehole or into a large waste chamber in the tool 100 until the fluid being withdrawn becomes sufficiently clean. A clean sample is one where the concentration of mud filtrate in the sample fluid is acceptably low so that the fluid substantially represents native (i.e., naturally occurring) formation fluids. In the illustrated example, the tool 100 is provided with fluid collecting chambers 122 and 123 to store collected fluid samples.

[0043] The tool of FIG. 2A is adapted to make in-situ determinations regarding hydrocarbon bearing geological formations by downhole sampling of reservoir fluid at one or more measurement stations within the borehole 112, conducting downhole fluid analysis of one or more reservoir fluid samples for each measurement station (including compositional analysis, such as estimating concentrations of a plurality of compositional components of a given sample, as well as other fluid properties), and relating the downhole fluid analysis to an equation of state (EOS) model of the thermodynamic behavior of the fluid in order to characterize the reservoir fluid at different locations within the reservoir. With the reservoir fluid characterized with respect to its thermodynamic behavior, fluid production parameters, transport properties, and other commercially useful indicators of the reservoir can be computed.

[0044] For example, the EOS model can provide the phase envelope that can be used to interactively vary the rate at which samples are collected in order to avoid entering the two-phase region. In another example, the EOS can provide useful properties in assessing production methodologies for the particular reserve. Such properties can include density, viscosity, and volume of gas formed from a liquid after expansion to a specified temperature and pressure. The characterization of the fluid sample with respect to its thermodynamic model can also be used as a benchmark to determine the validity of the obtained sample, whether to retain the sample, and/or whether to obtain another sample at the location of interest. More particularly, based on the thermodynamic model and information regarding formation pressures, sampling pressures, and formation temperatures, if it is determined that the fluid sample was obtained near or below the bubble line of the sample, a decision may be made to jettison the sample and/or to obtain a sample at a slower rate (i.e., a smaller pressure drop) so that gas will not evolve out of the sample. Alternatively, because knowledge of the exact dew point of a retrograde gas condensate in a formation is desirable, a decision may be made, when conditions allow, to vary the pressure drawdown in an attempt to observe the liquid condensation and thus establish the actual saturation pressure.

[0045] FIG. 2B illustrates an exemplary embodiment of the fluid analysis module 125 of

FIG. 2A (labeled 125'), including a probe 202 having a port 204 to admit formation fluid therein.

A hydraulic extending mechanism 206 may be driven by a hydraulic system 220 to extend the probe 202 to sealingly engage the formation 114 (FIG. 2A). In alternative implementations, more than one probe can be used or inflatable packers can replace the probe(s) and function to establish fluid connections with the formation and sample fluid samples.

[0046] The probe 202 can be realized by the Quicksilver Probe available from Schlumberger Technology Corporation. The Quicksilver Probe divides the fluid flow from the reservoir into two concentric zones, a central zone isolated from a guard zone about the perimeter of the central zone. The two zones are connected to separate flowlines with independent pumps. The pumps can be run at different rates to exploit filtrate/fluid viscosity contrast and permeability anistrotropy of the reservoir. Higher intake velocity in the guard zone directs contaminated fluid into the guard zone flowline, while clean fluid is drawn into the central zone. Fluid analyzers analyze the fluid in each flowline to determine the composition of the fluid in the respective flowlines. The pump rates can be adjusted based on such compositional analysis to achieve and maintain desired fluid contamination levels. The operation of the Quicksilver Probe efficiently separates contaminated fluid from cleaner fluid early in the fluid extraction process, which results in obtaining clean fluid in much less time than traditional formation testing tools.

[0047] The fluid analysis module 125' includes a flowline 207 that carries formation fluid from the port 204 through a fluid analyzer 208. The fluid analyzer 208 includes a light source that directs light to a sapphire prism disposed adjacent the flowline fluid flow. The reflection of such light is analyzed by a gas refractometer and dual fluoroscene detectors. The gas refractometer qualitatively identifies the fluid phase in the flowline. At the selected angle of incidence of the light emitted from the diode, the reflection coefficient is much larger when gas is in contact with the window than when oil or water is in contact with the window. The dual fluoroscene detectors detect free gas bubbles and retrograde liquid dropout to accurately detect single-phase fluid flow in the flowline 207. Fluid type is also identified. The resulting phase information can be used to define the difference between retrograde condensates and volatile oils, which can have similar GORs and live oil densities. It can also be used to monitor phase separation in real-time and ensure single-phase sampling. The fluid analyzer 208 also includes dual spectrometers - a filter array spectrometer and a grating-type spectrometer.

[0048] The filter-array spectrometer of the analyzer 208 includes a broadband light source providing broadband light that passes along optical guides and through an optical chamber in the flowline to an array of optical density detectors that are designed to detect narrow frequency bands (commonly referred to as channels) in the visible and near-infrared spectra as described in US Patent 4,994,671, incorporated herein by reference in its entirety. Preferably, these channels include a subset of channels that detect water absorption peaks (which are used to characterize water content in the fluid) as well as a dedicated channel corresponding to the absorption peak of C0₂ with dual channels above and below this dedicated channel that subtract out the overlapping spectrum of hydrocarbon and small amounts of water (which are used to characterize C0₂ content in the fluid). The filter array spectrometer also employs optical filters that provide for identification of the color (also referred to as "optical density" or "OD") of the fluid in the flowline. Such color measurements support fluid identification, determination of asphaltene content, and PH measurement. Mud filtrates or other solid materials generate noise in the channels of the filter array spectrometer. Scattering caused by these particles is independent of wavelength. In the preferred embodiment, the effect of such scattering can be removed by subtracting a nearby channel.

[0049] The grating-type spectrometer of the analyzer 208 is designed to detect channels in the near-infrared spectra (preferably between 1600-1800 nm) where reservoir fluid has absorption characteristics that reflect molecular structure.

[0050] The analyzer 208 also includes a pressure sensor for measuring pressure of the formation fluid in the flowline 207, a temperature sensor for measuring temperature of the formation fluid in the flowline 207, and a density sensor for measuring live fluid density of the fluid in the flowline 207. In the preferred embodiment, the density sensor is realized by a vibrating sensor that oscillates in two perpendicular modes within the fluid. Simple physical models describe the resonance frequency and quality factor of the sensor in relation to live fluid density. Dual-mode oscillation is advantageous over other resonant techniques because it minimizes the effects of pressure and temperature on the sensor through common mode rejection. In addition to density, the density sensor can also provide a measurement of live fluid viscosity from the quality factor of oscillation frequency. Note that live fluid viscosity can also be measured by placing a vibrating object in the fluid flow and measuring the increase in line width of any fundamental resonance. This increase in line width is related closely to the viscosity of the fluid. The change in frequency of the vibrating object is closely associated with the mass density of the object. If density is measured independently, then the determination of viscosity is more accurate because the effects of a density change on the mechanical resonances are determined. Generally, the response of the vibrating object is calibrated against known standards. The analyzer 208 can also measure resistivity and pH of fluid in the flowline 207. In the preferred embodiment, the fluid analyzer 208 is realized by the InSitu Fluid Analyzer available from Schlumberger Technology Corporation. In other exemplary implementations, the flowline sensors of the analyzer 208 may be replaced or supplemented with other types of suitable measurement sensors (e.g., NMR sensors, capacitance sensors, etc.). Pressure sensor(s) and/or temperature sensor(s) for measuring pressure and temperature of fluid drawn into the flowline 207 can also be part of the probe 202.

[0051 ] A pump 228 is fluidly coupled to the flowline 207 and is controlled to draw formation fluid into the flowline 207 and to supply formation fluid to the fluid collecting chambers 122 and 123 (FIG. 2A) via valve 229 and flowpath 231 (FIG. 2B).

[0052] The fluid analysis module 125' includes a data processing system 213 that receives and transmits control and data signals to the other components of the module 125' for controlling operations of the module 125'. The data processing system 213 also interfaces with the fluid analyzer 208 for receiving, storing and processing the measurement data generated therein. In the preferred embodiment, the data processing system 213 processes the measurement data output by the fluid analyzer 208 to derive and store measurements of the hydrocarbon composition of fluid samples analyzed in-situ by the fluid analyzer 208, including

- flowline temperature;

- flowline pressure;

- live fluid density (p) at the flowline temperature and pressure;

- live fluid viscosity (μ) at flowline temperature and pressure;

- concentrations (e.g., weight percentages) of carbon dioxide (C0₂), methane (CH₄), ethane (C₂H₆), the C3-C5 alkane group, the lump of hexane and heavier alkane components (C6+), and asphaltene content;

- GOR; and - possibly other parameters (such as API gravity and formation volume factor (FVF)).

[0053] Flowline temperature and pressure is measured by the temperature sensor and pressure sensor, respectively, of the fluid analyzer 208 (and/or probe 202). In the preferred embodiment, the output of the temperature sensor(s) and pressure sensor(s) are monitored continuously before, during, and after sample acquisition to derive the temperature and pressure of the fluid in the flowline 207. The formation temperature is not likely to deviate substantially from the flowline temperature at a given measurement station and thus can be estimated as the flowline temperature at the given measurement station in many applications. Formation pressure can be measured by the pressure sensor of the fluid analyzer 208 in conjunction with the downhole fluid sampling and analysis at a particular measurement station after buildup of the flowline to formation pressure.

[0054] Live fluid density (p) at the flowline temperature and pressure is determined by the output of the density sensor of the fluid analyzer 208 at the time the flowline temperature and pressure is measured.

[0055] Live fluid viscosity (μ) at flowline temperature and pressure is derived from the quality factor of the density sensor measurements at the time the flowline temperature and pressure are measured.

[0056] The measurements of the hydrocarbon composition of fluid samples are derived by translation of the data output by spectrometers of the fluid analyzer 208.

[0057] The GOR is determined by measuring the quantity of methane and liquid components of crude oil using near infrared absorption peaks. The ratio of the methane peak to the oil peak on a single phase live crude oil is directly related to GOR.

[0058] The fluid analysis module 125' can also detect and/or measure other fluid properties of a given live oil sample, including retrograde dew formation, asphaltene precipitation, and/or gas evolution.

[0059] The fluid analysis module 125' also includes a tool bus 214 that communicates data signals and control signals between the data processing system 213 and the surface-located electrical control system 118 of FIG. 2A. The tool bus 214 can also carry electrical power supply signals generated by a surface-located power source for supply to the module 125', and the module 125' can include a power supply transformer/regulator 215 for transforming the electric power supply signals supplied via the tool bus 214 to appropriate levels suitable for use by the electrical components of the module 125'.

[0060] Although the components of FIG. 2B are shown and described above as being communicatively coupled and arranged in a particular configuration, persons of ordinary skill in the art will appreciate that the components of the fluid analysis module 125' can be

communicatively coupled and/or arranged differently than depicted in FIG. 2B without departing from the scope of the present disclosure. In addition, the example methods, apparatus, and systems described herein are not limited to a particular conveyance type but, instead, may be implemented in connection with different conveyance types including, for example, coiled tubing, wireline, wired drill pipe, and/or other conveyance means known in the industry.

[0061 ] In accordance with the present invention, the system of FIGS. 2A and 2B can be employed as part of the methodology of FIGS. 3 A - 3B to characterize the fluid properties of a petroleum reservoir of interest. As will be appreciated by those skilled in the art, the surface- located electrical control system 118 and the fluid analysis module 125 of the tool 100 each include data processing functionality (e.g., one or more microprocessors, associated memory, and other hardware and/or software) that cooperate to implement the invention as described herein. The electrical control system 118 can also be realized by a distributed data processing system wherein data measured by the tool 100 is communicated in real-time over a

communication link (typically a satellite link) to a remote location for data analysis as described herein. The data analysis can be carried out on a workstation or other suitable data processing system (such as a computer cluster or computing grid).

[0062] The operations of FIGS. 3A - 3B begin in step 301 by employing the DFA tool 100 of FIGS. 2A and 2B to obtain a sample of the formation fluid at the reservoir pressure and temperature (a live oil sample) at a measurement station in the wellbore (for example, a reference station), and the sample is processed by the fluid analysis module 125 (stages 10 and 12 of FIG. 1). In the preferred embodiment, the fluid analysis module 125 performs spectrophotometry measurements that measure absorption spectra of the live oil sample and translates such spectrophotometry measurements into concentrations of several alkane components and groups in the fluids of interest. In an illustrative embodiment, the fluid analysis module 125 provides measurements of the concentrations (e.g., weight percentages) of carbon dioxide (C0₂), methane (CH₄), ethane (C₂H₆), the C3-C5 alkane group including propane, butane, pentane, the lump of hexane and heavier alkane components (C6+), and asphaltene content. The tool 100 also preferably provides a means to measure temperature of the fluid sample (and thus reservoir temperature at the station), pressure of the fluid sample (and thus reservoir pressure at the station), live fluid density of the fluid sample, live fluid viscosity of the fluid sample, gas-oil ratio (GOR) of the fluid sample, optical density, and possibly other fluid parameters (such as API gravity and formation volume factor (FVF)) of the fluid sample. The results of the downhole fluid analysis of step 301 are stored in the data store 14 for subsequent use.

[0063] In step 301, the tool 100 is also controlled to collect and store one or more isolated live oil samples in fluid collecting chambers 122, 123 (FIG. 2A) of the tool (stage 10 of FIG. 1). The respective live oil sample is collected at reservoir conditions (at the formation temperature and pressure) and stored within a sealed sample container at these conditions for transport uphole to the wellsite when the tool is withdrawn from the wellbore.

[0064] The downhole fluid sampling and analysis operations of step 301 can be repeated for additional measurement stations within the wellbore as desired.

[0065] In step 302, the results of the compositional analysis of step 301 are used to predict compositional gradients and other property gradients within the wellbore (stage 26). Such composition analysis is performed in real-time in conjunction with the downhole fluid analysis of step 301 in order to provide guidance as to the accuracy and effectiveness of the downhole fluid analysis and make as a decision as to whether additional downhole fluid analysis is necessary. In the preferred embodiment, the operations of step 302 involve a delumping process that characterizes the compositional components of the live oil sample analyzed by DFA in step 301. The delumping process splits the concentration (e.g., mass fraction, which is sometimes referred to as weight fraction) of given compositional lumps (C3-C5, C6+) into concentrations (e.g., mass fractions) for single carbon number (SCN) components of the given compositional lump (e.g., split C3-C5 lump into C3, C4, C5, and split C6+ lump into C6, C7, C8 ...). Details of the exemplary delumping operations carried out as part of step 302 are described in detail in Patent Application Publication US 2009/0192768, incorporated herein by reference in its entirety. The results of the delumping process are used in conjunction with an equation of state (EOS) model (and possibly other predictive models) to predict compositions and fluid properties (such as volumetric behavior of oil and gas mixtures) as a function of depth in the reservoir. The predictions can include property gradients, pressure gradients, and temperature gradients of the reservoir fluid as a function of depth. The property gradients preferably include mass fractions, mole fractions, molecular weights, and specific gravities for a set of components (such as single carbon number components and heavy fractions including resins and asphaltenes) as a function of depth in the reservoir. Details of exemplary operations for prediction of composition gradients are described in PCT Patent Application PCT/IB2010/053620. Other suitable reservoir property modelling schemes can be used.

[0066] In step 303, the predictions of compositional gradients generated in step 302 are used to identify a potential flow barrier (low permeability) within the wellbore as well as the depth interval of the potential flow barrier. A potential flow barrier can be indicated by discontinuous GOR (or if lower GOR is found higher in the column), discontinuous resin and/or asphaletene content (or if higher resin and/or asphaltene content is found higher in the column),

discontinuous fluid density and/or fluid viscosity (or if higher fluid density and/or fluid viscosity is found higher in the column), or other suitable fluid properties. Downhole log data from stage 22 can characterize natural radioactivity, formation density, formation porosity, electrical resistivity and other suitable rock characteristics. The measurements can be interpreted to identify a potential flow barrier within the wellbore as well as the depth interval of the potential flow barrier.

[0067] In step 305, a coring tool is deployed within the wellbore traversing the reservoir of interest and operated to extract one or more core samples (stage 16). In one embodiment, the coring tool obtains one or more sidewall cores from the formation adjacent the wellbore as described above with respect to stage 16, although whole cores may also be obtained while drilling the wellbore. The core samples are obtained from the formation over the depth interval of the potential flow barrier identified in step 303. Core samples can be obtained from other depths within the wellbore as desired. If need be, additional live oil samples can be collected at or near the depth of the potential flow barrier identified in step 303.

[0068] In step 307, the live oil samples collected in step 301 as well as the core samples collected in step 305 are validated at the wellsite. Such wellsite validation can involve inspection of the condition of the live oil sample containers and core sample containers, measurement of live oil sample container opening pressure, and comparison of the wellsite pressure measurements to corresponding downhole fluid pressure measurements. If there are anomolies between these measurements, the process may be restarted.

[0069] Once validated in step 307, the live oil samples and core samples are transported to the laboratory in step 309.

[0070] In step 311, the downhole fluid analysis measurements of step 301 are optionally reproduced in the laboratory for chain-of-custody analysis (stage 18). More specifically, the live oil sample is reconditioned to the formation reservoir and pressure at the sample depth (as dictated by the DFA data stored in the data store 14). The reconditioned live oil sample is then subjected to analytical measurements (e.g., GOR, oil-based mud contamination, fluid composition) that replicate the downhole fluid analysis measurements. In step 313, the results of the laboratory measurements of step 311 are compared to the results of the corresponding downhole measurements of step 301 and stored as part of the DFA data in data store 14. If there is agreement between the downhole and laboratory fluid measurements, the operations continue to step 315. If there is disagreement between the downhole and laboratory fluid measurements, the sample and the laboratory measurements based thereon can be discarded or otherwise ignored. In the case of failure, actions can be taken to identify and correct the cause of the failure, which can arise from hardware failure of the downhole fluid analysis tool or laboratory tool, and inappropriate sampling, sample reconditioning, and/or sample transfer techniques.

[0071 ] In optional step 315, additional laboratory composition analysis and/or other property analysis can be performed on one or more live oil samples (stage 20). For example, such laboratory analysis can employ high resolution compositional analysis of the live oil samples as described above with respect to stage 20. Such laboratory analysis can be used to verify the compositions predicted by the downhole fluid analysis and modeling based thereon and to provide a more complete understanding of the reservoir fluids.

[0072] In step 317, each core sample is analyzed in the laboratory and the results of the analysis are stored in the data store 14 (stage 20). Such analysis can include bulk measurements

(e.g., porosity, grain density, permeability, and residual saturation) to measure properties of the core sample. In the case that the core sample includes movable hydrocarbons, hydrocarbon fluid is extracted from the core sample (preferably by centrifuging the core sample). In the case that the core sample includes non-movable bitumen, hydrocarbon fluid can be extracted from the bitumen core sample using a suitable solvent such as toluene, chloroform, or methane chloride.

In either case, the composition of the extracted hydrocarbon fluid is characterized by geochemical analysis in step 319 and the results of the geochemical analysis are stored in the data store 14 (stage 20). The geochemical analysis of step 319 can be carried out by a variety of techniques as described above with respect to stage 20. The laboratory analysis of step 319 can also employ high resolution compositional analysis of the core extract as described above with respect to stage 20.

[0073] In step 321, the compositions of the core sample extract as measured and stored in the data store 14 in step 319 are compared to the compositions (particularly the incompatible fluid- insoluble fractions and possibly other fractions) of the live oil sample as measured in step 311 (and/or step 301 or step 315) and stored in data store 14.

[0074] In step 323, the comparison of step 321 is used to infer structure (or other properties) of the reservoir of interest. An example of such analysis is shown in Figure 4.

[0075] In step 403, the chemical composition (fingerprint) of the bitumen core sample extract is compared to the chemical composition of the incompatible fluid-insoluble fraction of the live oil sample(s) (or that of the formation fluid measured by DFA) at or near the depth of the bitumen core sample from which the extract was produced. If these compositions are similar, the operations continue to step 405; otherwise the operations continue to step 407.

[0076] In step 405, it is interfered that the non-movable bitumen layer of the reservoir was likely formed by a late incompatible fluid charge. In this case, the non-movable bitumen layer is located in the portions of the reservoir that are below those portions exposed to the incompatible fluid charge. Such locations (or hints at these locations) can be depicted visually as part of a basin model or added thereto for visualization purposes, or otherwise communicated to interested parties/entities. The operations then continue to step 411.

[0077] In step 407, the composition of the bitumen core extract is analyzed to identify the the presence of biomarkers indicative of biodegradation. Examples of such biomarkers in the core extract include 25-norphases, hopanes, steranes, and organic acids with low acyclic: cyclic ratios. The presence of such biomarkers can be measured in the laboratory in step 319 by gas chromatography with various columns (packed column, capillary columns) and detectors (flame- ionization detector, thermal conductivity detector, mass spectrometer), and by high resolution mass spectrometry. If such biomarkers are present in the bitumen core extract, the operations continue to step 409; otherwise, the operations continue to step 411.

[0078] In step 409, it is inferred that the non-movable bitumen layer of the reservoir was likely formed by degradation. In this case, the non-movable bitumen layer is located in the portions of the reservoir at a current or past water-oil contact and thus conductive to

biodegradation. Such locations (or hints at these locations) can be depicted visually as part of a basin model or added thereto for visualization purposes or otherwise communicated to interested parties/entities. The operations then continue to step 411.

[0079] In optional step 411, additonal analysis and/or modeling can be performed to better characterize and understand the reservoir of interest for reservoir assessment, planning and management. Such analysis and/or modeling may include basin modeling, integration with petrophysical logs, or integration with traditional geochemical analyses.

[0080] There have been described and illustrated herein a preferred embodiment of a method, system, and apparatus for downhole fluid analysis of a reservoir of interest and for characterizing the reservoir of interest based upon such downhole fluid analysis and follow-on laboratory analysis. While particular embodiments of the invention have been described, it is not intended that the invention be limited thereto, as it is intended that the invention be as broad in scope as the art will allow and that the specification be read likewise. Thus, while particular downhole tools and analysis techniques have been disclosed for characterizing properties of the reservoir fluid and surrounding formation, it will be appreciated that other tools and analysis tehniques could be used as well. Moreover, the methodology described herein is not limited to stations in the same wellbore. For example, measurements from samples from different wells can be analyzed as described herein for testing for lateral connectivity. In addition, the workflow as described herein can be modified. It will therefore be appreciated by those skilled in the art that yet other modifications could be made to the provided invention without deviating from its scope as claimed.

Claims

CLAIMS What is claimed is:

1. A method for characterizing a hydrocarbon reservoir traversed by a wellbore, the method comprising:

(a) for at least one location within the wellbore, performing downhole fluid sampling operations to collect a hydrocarbon fluid sample at the location;

(b) performing core sampling operations to collect at least one core sample at a location identified as a potential flow barrier in the reservoir;

(c) performing laboratory analysis that analyzes the composition of the hydrocarbon fluid sample collected in (a);

(d) performing laboratory operations that extract fluid from the at least one core sample collected in (b);

(e) performing laboratory operations that analyze the composition of the fluid extracted in (d); and

(f) comparing the compositions of the hydrocarbon fluid sample derived in (c) and the compositions of the extracted fluid derived in (e) to characterize properties of the reservoir of interest.

2. A method according to claim 1, further comprising: performing downhole fluid analysis on live hydrocarbon fluids corresponding to the hydrocarbon fluid sample collected in (a) and storing the results of such analysis; and before (b), validating chain-of-custody of the hydrocarbon fluid sample by performing laboratory fluid analysis on the hydrocarbon fluid sample that reconstructs the downhole fluid analysis performed on the corresponding live hydrocarbon fluid and comparing the results of the laboratory fluid analysis and the stored results of the corresponding downhole fluid analysis.

3. A method according to claim 2, wherein the laboratory fluid analysis for validating chain-of- custody of the hydrocarbon fluid sample comprises the laboratory analysis of (c).

4. A method according to claim 2, wherein the laboratory analysis of (c) is different than the laboratory fluid analysis for validating chain-of-custody of the hydrocarbon fluid sample.

5. A method according to claim 4, wherein the laboratory analysis of (c) employs compositional analysis of the hydrocarbon fluid sample that is higher in resolution as compared to the laboratory fluid analysis for validating chain-of-custody of the hydrocarbon fluid sample.

6. A method according to claim 1, further comprising: performing downhole fluid analysis over a number of locations in the wellbore, and using the results of such downhole fluid analysis to predict compositional gradients within the reservoir; evaluating the results of such downhole fluid analysis and/or the compositional gradients based thereon to identify the location of the potential flow barrier in the reservoir; performing downhole fluid sampling operations that collect at least one isolated live hydrocarbon fluid sample at or near the location of the potential flow barrier in the reservoir; and transporting the at least one isolated live hydrocarbon fluid sample to at least one laboratory for analysis.

7. A method according to claim 1, wherein results of the laboratory analysis of (c) and results of the laboratory analysis of (e) are stored in a central database.

8. A method according to claim 1, wherein the properties of the reservoir of interest

characterized in (f) are used to determine reservoir architecture.

9. A method according to claim 1, wherein the properties of the reservoir of interest

characterized in (f) are used to determine reservoir structure.

10. A method according to claim 1, wherein the properties of the reservoir of interest characterized in (f) are used as part of basin model operations.

11. A method according to claim 1 , wherein the at least one core sample is a sidewall core.

12. A method according to claim 1, wherein the at least one core sample is a whole core.

13. A method according to claim 1, wherein the analysis of (c) defines the compositional properties of the incompatible fluid-insoluble fraction of the hydrocarbon fluid sample, and wherein the fluid extracted from the core sample in (d) is bitumen, and the comparing of (f) compares the compositional properties of the core sample extract as derived in (e) to those of the incompatible fluid-insoluble fraction of the hydrocarbon fluid.

14. A method according to claim 13, wherein in the event that there are similarities between the compositional properties of the core sample extract as derived in (e) and those of the

incompatible fluid-insoluble fraction of the hydrocarbon sample as derived in (c), inferring that it is likely that the bitumen of the core sample formed by a late incompatible fluid charge.

15. A method according to claim 14, further comprising inferring from the similarities in compositional properties that a bitumen layer is disposed below portions of the reservoir of interest exposed to the incompatible fluid charge.

16. A method according to claim 13, wherein: in the event that the compositional properties of the core sample extract as derived in (e) are different from those of the incompatible fluid-insoluble fraction of the hydrocarbon sample as derived in (c), analyzing the compositional properties of the core sample extract for the presence of biomarkers indicative of high levels of biodegradation; and in the event that biomarkers indicative of high levels of biodegradation are present, inferring that it is likely that the bitumen of the core sample formed by biodegradation.

17. A method according to claim 16, further comprising inferring from the difference in compositional properties that a bitumen layer is disposed in portions of the reservoir of interest conductive to biodegradation.

18. A method according to claim 13, wherein the incompatible fluid comprises gas, carbon dioxide, or condensate.