Determining source rock maturity based on hydrogen isotopes

Abstract

A computer receives a measured wetness of and a measured δ2H value associated with a test gas sample from a hydrocarbon formation. The measured wetness is a molar ratio of heavy gas compounds over a total gas within the measured sample. The computer receives calculated wetnesses calculated δ2H values associated with a gas samples taken from one or more analogous hydrocarbon reservoirs. The measured wetness received for the test gas sample is identified from among the plurality of calculated wetnesses. The computer determines a corresponding δ2H value from among the calculated δ2H values that corresponds to the measured wetness of the test gas sample. The computer determines a predicted sample VRo (vitrinite reflectance equivalent) for the test gas sample based on the corresponding δ2H value and a correlation of δ2H values to VRo values. Hydrocarbons are produced from the hydrocarbon formation based on the predicted sample VRo.

Description

TECHNICAL FIELD

This disclosure relates to determining maturity of source rocks in geologic formations.

BACKGROUND

Hydrogen isotopes of natural gas can be utilized to calculate maturity of gas and source rocks found within a geologic formation. The maturity of either the gas or the source rock can be an indication of the suitability of the geologic formation for hydrocarbon production. As kerogen is progressively cracking, kinetic effects on isotopic fractionation result in two normal trends in light gaseous compounds from conventional gas fields. For example, the isotope ratio of Hydrogen 2 to Hydrogen 1 increases relative to a standard (this ratio is expressed as δ²H) as maturity increases.

SUMMARY

This disclosure describes technologies relating to determining source rock maturity based on hydrogen isotopes.

An example of the subject matter described within this disclosure is a method with the following features. A computer receives a measured wetness of and a measured δ²H value associated with a test gas sample from a hydrocarbon formation. The measured wetness is a molar ratio of heavy gas compounds over a total gas within the measured sample. The computer receives calculated wetnesses calculated δ²H values associated with a gas samples taken from one or more analogous hydrocarbon reservoirs that are analogous to the hydrocarbon formation. The calculated wetness is a molar ratio of heavy gas compounds over a total gas within each of the plurality of gas samples. The measured wetness received for the test gas sample is identified from among the plurality of calculated wetnesses. The computer determines a corresponding δ²H value from among the calculated δ²H values that corresponds to the measured wetness of the test gas sample. The computer determines a predicted sample VR_o (vitrinite reflectance equivalent) for the test gas sample based on the corresponding δ²H value and a correlation of δ²H values to VR_o values. The VR_o values correlate to gas maturity. Hydrocarbons are produced from the hydrocarbon formation by a hydrocarbon production system based on the predicted sample VR_o.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. Determining the corresponding δ²H value from among the calculated δ²H values includes determining an equation to best fit the calculated δ²H values and the calculated wetnesses. The equation is used to create a reference line. A plot is generated with the reference line by the computer. The plot has a Y-axis representative of a range of the calculated δ²H values and an X-axis representative of a range of calculated wetnesses. The measured wetness is identified on the plot. A δ²H value corresponding to the measured wetness is identified from the reference line.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The equation is:δ²H(C₁)=−0.35W−114.5where δ²H(C₁) corresponds to values of δ²H of methane in the plurality of gas samples, and “W” corresponds to the plurality of calculated wetnesses of the plurality of gas samples.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The measured wetness is determined to be within a specified range of values. The specified range of values is indicative of an isotopic reversal.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The specified range of values for the measured wetness ranges 0% through 7%.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The measured wetness is determined to be above a specified threshold value. The specified threshold is a threshold indicative of a lack of isotopic reversal.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The specified value for the measured wetness is above 7%.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The measured wetness of the test gas sample is determined by a gas chromatograph.

An example of the subject matter described within this disclosure is a method with the following features. A test gas sample is received from a wellbore within a test hydrocarbon formation. A measured wetness of the test gas sample is determined. A measured δ²H value associated with the test gas sample is determined. Calculated δ²H values are received from a gas samples with a corresponding calculated wetnesses of gas samples. The gas samples are taken from one or more analogous hydrocarbon formations that are analogous to the test hydrocarbon formation. The measured wetness of the test gas sample is identified from the calculated wetnesses. A corresponding δ²H value is determined from among the calculated δ²H values that corresponds to the measured wetness of the test gas sample. The measured δ²H value is adjusted to equal the corresponding δ²H value to provide an adjusted δ²H value. A predicted sample VR_o (vitrinite reflectance equivalent) is determined for the test gas sample based on the adjusted δ²H value and a correlation of δ²H values to VR_o values. The VR_o values correlate with a gas maturity. Hydrocarbons are produced from the hydrocarbon formation based on the predicted sample VR_o.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. Determining the corresponding δ²H value from among the calculated δ²H values comprises determining a best-fit equation from the calculated δ²H values and the plurality of calculated wetnesses. The best-fit equation is used to create a reference line.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The best-fit equation is:δ²H(C₁)=−0.35W−114.5where δ²H(C₁) corresponds to values of δ¹³C of methane in the gas samples and “W” corresponds to the calculated wetnesses of the plurality of gas samples.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The measured wetness is determined to be below a threshold value. Being at or below the threshold value is indicative of an isotopic reversal.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The threshold value for the measured wetness is 7%.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The measured wetness of the test gas sample is determined by a gas chromatograph.

An example of the subject matter described within this disclosure is a method with the following features. A computer system receives a dataset comprising calculated wetnesses of and calculated δ²H values associated with hydrocarbon gasses. The computer system determines a reference line from the dataset. The computer plots the reference line on a plot. The computer plots a sample wetness of and a sample δ²H value associated with a received gas sample received from a hydrocarbon formation on the plot with the reference line to produce a plotted point. The computer system increases a δ²H value of the plotted point to provide an adjusted plotted point so that a δ²H value of the adjusted plotted point matches the reference line. The computer system determines an adjusted δ²H value from the adjusted plotted point. The adjusted δ²H value is the δ²H value of the adjusted plotted point. The computer system determines a predicted sample VR_o (vitrinite reflectance equivalent) for the received gas sample based on the adjusted δ²H value and a correlation of δ²H values to VR_o values. The VR_o values correlate with gas maturity.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The determined predicted sample VR_o correlates to a maturity level associated with hydrocarbon presence. Hydrocarbons are produced from the hydrocarbon formation based on the correlated gas maturity.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. A difference between the sample wetness and the reference line is determined to exceed a specified threshold.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The threshold is greater than or equal to a 10% difference.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The reference line is defined by:δ²H(C₁)=−0.35W−114.5where δ²H(C₁) corresponds to values of δ²H of methane in the dataset and “W” corresponds to the calculated wetnesses in the dataset.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. The wetness of the received gas sample is determined by a gas chromatograph.

Aspects of the example method, which can be combined with the example method alone or in combination with other aspects, include the following. Wetness is defined by the following equation:W=100(C2+C3+C4+C5)/(C1+C2+C3+C4+C5)where “W” is a wetness percentage, where “C1” is a molar percentage of methane within a hydrocarbon gas, where “C2” is a molar percentage of ethane within the hydrocarbon gas, where “C3” is a molar percentage of propane within the hydrocarbon gas, where “C4” is a molar percentage of butane within the hydrocarbon gas, and where C5 is a molar percentage of pentane within the hydrocarbon gas.

Particular implementations of the subject matter described in this disclosure can be implemented so as to realize one or more of the following advantages. Correcting δ²H values results in more accurate maturity assessments and fewer resulting miss-drilled production wells. In other words sweet spots for either oil, wet gas or dry gas, can be determined based on maturity correctly determined by hydrogen isotopes will help plan operations of exploration and production.

The details of one or more implementations of the subject matter described in this disclosure are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages of the subject matter will become apparent from the description, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of a method that can be used with aspects of this disclosure.

FIG. 2 is a plot of δ²H values versus wetness values.

FIG. 3 is an annotated plot of δ²H values versus wetness values.

FIG. 4 is a block diagram of an example processing system.

Like reference numbers and designations in the various drawings indicate like elements.

DETAILED DESCRIPTION

In some instances, hydrogen isotope ratios in light gas compounds from unconventional shale gas do not change linearly. Instead, the linear trend reverses as maturity increases in certain instances. The phenomena can occur in unconventional tight shale, sandstone, and in conventional gas fields. In the context of this disclosure, high maturity can be at least Vitrinite Reflectance Equivalent (VR_o)=2.0% for example. In an unconventional reservoir, when VR_o>2.0%, an isotope reversal can occur. Over mature gas, in the context of this disclosure, VR_o>3%. However, this range can extend between 2.5% to 3.5% depending on the reservoir. When isotopic reversal occurs, the measured δ²H value does not always correspond to a corresponding VR_o within a look-up table. That is, maturity cannot be calculated by using isotopes from δ²H values and corresponding look-up tables directly.

This disclosure relates to correcting reversed hydrogen isotopes of gases, and then applying the corrected isotope values to a look-up table to calculate gas maturity using a corrected δ²H value. To do so, a relationship between wetness and hydrogen isotopes is established. As maturity increases, wetness of natural gas decreases. As a result, wetness can be used as an indicator for maturity. As wetness decreases, δ²H values generally increase based on data from conventional and unconventional gas fields. When in the region of high wetness (for example, wetness>15%) and low maturity, hydrogen isotopes of methane increase linearly as wetness decreases. As wetness continuously decreases, δ²H values of methane generally increase, but isotope reversal occurs particularly when wetness is <7%. That is, rather than δ²H values increasing, δ²H values drop or reverse the increasing trend around the aforementioned wetness. Because of the reversal, if a δ²H value in this range is applied to look-up table, the resulting calculated maturity would be incorrect.

FIG. 1 is a flowchart of a method 100 that can be used with aspects of this disclosure. In some implementations, aspects of the method 100 are performed by a computer. At 102, a measured wetness of and a measured δ²H value associated with a test gas sample from a hydrocarbon formation, is received. In some implementations, such data are received by a computer. In some implementations, such information is acquired after receiving a test gas sample from a wellbore within a test hydrocarbon formation and determining a measured wetness and a measured δ²H value of the test gas sample. The measured wetness is a molar ratio of heavy gas compounds over a total gas within the measured sample. That is, the wetness is defined by equation 1 below:W=100(C2+C3+C4+C5)/(C1+C2+C3+C4+C5)  (1)where “W” is a wetness percentage, where “C1” is a molar percentage of methane within a hydrocarbon gas, where “C2” is a molar percentage of ethane within the hydrocarbon gas, where “C3” is a molar percentage of propane within the hydrocarbon gas, where “C4” is a molar percentage of butane within the hydrocarbon gas, and where “C5” is a molar percentage of pentane within the hydrocarbon gas. In some implementations, the measured wetness of the test gas sample is determined by a gas chromatograph.

δ²H is a ratio of Hydrogen 2 isotopes (that is, hydrogen atoms with a proton and a neutron) to Hydrogen 1 isotopes (that is, hydrogen with a single proton and no neutron) compared to a set standard. For example, δ²H can be defined by the following equation:δ²H(‰)=((²H/¹H)_sample/(²H/¹H)_VSMOW)−1)*1000  (2)where (²H/¹H) sample is the molar ratio of hydrogen 2 to hydrogen 1 (hydrogen with no neutrons), and where (²H/¹H)_VSMOW is the molar ratio of hydrogen 2 to hydrogen 1 within a standard gas composition. As illustrated and described within this disclosure, the Vienna Standard Mean Ocean Water is used; however, other standards can be used without departing from this disclosure.

At 104, a plurality of calculated wetnesses of and a plurality of calculated δ²H values are received. This dataset is associated with a plurality of gas samples taken from one or more analogous hydrocarbon reservoirs that are analogous to the hydrocarbon formation. That is, the analogous hydrocarbon reservoir has characteristics similar to the hydrocarbon formation. In some implementations, the dataset including the calculated wetnesses of and a plurality of calculated δ²H values, is received by a computer.

The method described in FIG. 1 is now described with reference to FIG. 2. FIG. 2 is a plot 200 of δ²H values versus wetness values. In some implementations, an equation determining to best fit the calculated δ²H values and the calculated wetnesses is determined by a computer. This equation, which in some implementations is determined by a computer, is then used to create a reference line 202. The plot 200 is generated with the reference line 202. In some implementations, the plot is generated and produced by the computer 402 (See FIG. 4). The plot has a Y-axis 204, representative of a range of the calculated δ²H values, and an X-axis 206 representative of a range of calculated wetnesses.

In some implementations, the equation for the reference (best-fit) line is:δ²H(C₁)=−0.35W−114.5  (3)where δ²H(C₁) corresponds to values of δ²H of methane in the gas samples, and “W” corresponds to the plurality of calculated wetnesses of the gas samples. In some implementations, such a reference line can be determined by the computer 402.

At 106, the measured wetness of the test gas sample is identified from the calculated wetnesses. There is a range 208 of wetness values in which an isotopic reversal occurs. In some instances, this range is between substantially 0% through 7%. In instances where the measured wetness is over 7%, a sample VR_o (vitrinite reflectance equivalent) for the test gas sample can be determined based on the measured δ²H, by looking up a corresponding VR_o value within a look-up table. The looked-up VR_o value correlates with gas maturity. VR_o is sometimes expressed as a percentage of light reflected back to a light detector. In general, the greater the percentage of light, the greater the maturity. Different types of hydrocarbons have different maturity windows (that is, ranges of reflected light) in which production is likely to occur. In general, the VR_o is correlated to the maximum burial heating (that is, the greatest temperature experiences by a sample in situ) of a sample. Various types of VR_o measurements can be used without departing from this disclosure. For example, random VR_o, maximum VR_o, minimum VR_o, or any combination can be used.

In instances when the range is within the 0-7% range, a range that is indicative of isotropic reversal, then a corrected δ²H is determined prior to determine the corresponding VR_o. Similarly, such correction can be useful when the measured δ²H value exceeds the best fit line, such as EQ. 3, by 10% or more. Such a correction process is illustrated in FIG. 3. FIG. 3 is an annotated plot 300 of δ²H values versus wetness values.

For the illustrated example, point “A” 302 is the point corresponding to the wetness value of the sample. That is, point “A” 302 has been identified from among the calculated wetnesses. As the wetness in this example falls within a range indicative of isotropic reversal, a correction is applied to the δ²H value.

That is, a δ²H value of the plotted point is increased, for example, by a computer, to provide an adjusted plotted point so that a δ²H value of the adjusted plotted point “B” 304 that matches the reference line 202. In other words, a δ²H value corresponding to the measured wetness is identified from the reference line, and the measured δ²H value is adjusted to equal the corresponding δ²H value to provide an adjusted δ²H value. That is, a corresponding δ²H value, from among the calculated δ²H values, corresponds to the measured wetness of the test gas sample. Based on the adjusted plotted point “B” 304, the new, adjusted δ²H value (point “C” 306) is determined. The adjusted δ²H value is then used to determine the VR_o value from within the look-up table.

At 110, a predicted sample VR_o for the test gas sample is determined based on the corresponding δ²H value and a correlation of δ²H values to VR_o values. As discussed throughout this disclosure, the VR_o values correlate with gas maturity. Such a determination can be made with a look-up table and can be performed, in some instances, by a computer.

Once a maturity is determined based on the corresponding VR_o value, an assessment is made as to whether or not the determined maturity corresponds with a specified hydrocarbon window. Assuming the determined maturity is within the desired window, or range, then, at 112, hydrocarbons are produced, by a hydrocarbon production system, from the hydrocarbon formation based on the predicted sample VR_o (maturity).

Implementations of the subject matter and the operations described in this disclosure can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this disclosure and their structural equivalents, or in combinations of one or more of them, for example, using computer 402. Implementations of the subject matter described in this disclosure can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions, encoded on computer storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively or in addition, the program instructions can be encoded on an artificially-generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. A computer storage medium can be, or be included in, a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them. Moreover, while a computer storage medium is not a propagated signal, a computer storage medium can be a source or destination of computer program instructions encoded in an artificially-generated propagated signal. The computer storage medium can also be, or be included in, one or more separate physical components or media (e.g., multiple CDs, disks, or other storage devices).

The operations described in this disclosure can be implemented as operations performed by a data processing apparatus on data stored on one or more computer-readable storage devices or received from other sources.

The term “data processing apparatus” encompasses all kinds of apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations, of the foregoing. The apparatus can include special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit). The apparatus can also include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them. The apparatus and execution environment can realize different computing model infrastructures, such as web services, distributed computing and grid computing infrastructures.

A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

The processes and logic flows described in this disclosure can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).

Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to, receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, e.g., a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive), to name just a few. Devices suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

To provide for interaction with a user, implementations of the subject matter described in this disclosure can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to and receiving documents from a device that is used by the user; for example, by sending web pages to a web browser on a user's client device in response to requests received from the web browser.

Implementations of the subject matter described in this disclosure can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this disclosure, or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network 432. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), an inter-network (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In some implementations, a server transmits data (e.g., an HTML page) to a client device (e.g., for purposes of displaying data to and receiving user input from a user interacting with the client device). Data generated at the client device (e.g., a result of the user interaction) can be received from the client device at the server.

An example of one such type of computer is shown in FIG. 4, which shows a block diagram of a programmable processing system (system) 410 suitable for implementing apparatus or performing methods of various aspects of the subject matter described in this disclosure. The system 410 includes the computer 402 coupled to a network 432. In some instances, a stand-alone, non-networked computer can be used without departing from this disclosure. The computer 402 includes a processor 420, a random-access memory (RAM) 421, a program memory 422 (for example, a writable read-only memory (ROM) such as a flash ROM), and a hard disk 430. The computer 402 can be preprogrammed, in ROM, for example, or it can be programmed (and reprogrammed) by loading a program from another source (for example, from a floppy disk, a CD-ROM, or another computer).

The hard disk 430 is suitable for storing executable computer programs, including programs embodying aspects of the subject matter described in this disclosure, and data including the dataset of wetnesses and δ²H values.

The I/O interface 427 receives and transmits data (e.g., stills, pictures, movies, and animations for importing into a composition) in analog or digital form over communication links such as a serial link, local area network, wireless link, and parallel link.

Also coupled to the I/O interface 427 can be a display, keyboard, or both (not all shown in FIG. 4). Alternatively or in addition, separate connections (separate buses) can be used for the I/O interface 427 and any peripheral components.

While this disclosure contains many specific implementation details, these should not be construed as limitations on the scope of what may be claimed, but rather as descriptions of features specific to particular implementations. Certain features that are described in this disclosure in the context of separate implementations can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. For example, the dataset of wetnesses and δ²H values can be received before, after, or at the same time as receiving the sample wetness and δ²H value. Moreover, the separation of various system components in the implementations described above should not be understood as requiring such separation in all implementations, and it should be understood that the described components and systems can generally be integrated together in a single product or packaged into multiple products.

Thus, particular implementations of the subject matter have been described. Other implementations are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results.

Claims

1. A method comprising: receiving, by a computer system, a dataset comprising calculated wetnesses of and calculated δ2H values associated with hydrocarbon gasses;determining, by the computer system, a reference line from the dataset;plotting, by the computer system, the reference line on a plot;plotting, by the computer system, a sample wetness of and a sample δ2H value associated with a received gas sample received from a hydrocarbon formation on the plot with the reference line to produce a plotted point;increasing, by the computer system, a δ2H value of the plotted point to provide an adjusted plotted point so that a δ2H value of the adjusted plotted point matches the reference line;determining, by the computer system, an adjusted δ2H value from the adjusted plotted point, wherein the adjusted δ2H value is the δ2H value of the adjusted plotted point; anddetermining, by the computer system, a predicted sample VRo (vitrinite reflectance equivalent) for the received gas sample based on the adjusted δ2H value and a correlation of δ2H values to VRo values, the VRo values correlating with gas maturity.

2. The method of claim 1, wherein the determined predicted sample VRo correlates to a maturity level associated with hydrocarbon presence, the method further comprising producing hydrocarbons from the hydrocarbon formation based on the correlated gas maturity.

3. The method of claim 1, wherein the reference line is defined by: δ2H(C1)=−0.35W−114.5where δ2H (C1) corresponds to values of δ2H of methane in the dataset, and “W” corresponds to the calculated wetnesses in the dataset.

4. The method of claim 1, further comprising determining the wetness of the received gas sample by a gas chromatograph.

5. The method of claim 1, wherein wetness is defined by the following equation: W=100(C2+C3+C4+C5)/(C1+C2+C3+C4+C5)where “W” is a wetness percentage, where “C1” is a molar percentage of methane within a hydrocarbon gas, where “C2” is a molar percentage of ethane within the hydrocarbon gas, where “C3” is a molar percentage of propane within the hydrocarbon gas, where “C4” is a molar percentage of butane within the hydrocarbon gas, and where C5 is a molar percentage of pentane within the hydrocarbon gas.

6. The method of claim 1, further comprising determining that a difference between the sample wetness and the reference line exceeds a specified threshold.

7. The method of claim 6, wherein the threshold is greater than or equal to a 10% difference.