Patent Application
20140254321
The present application relates generally to analysis of well logs, including simulated well logs, to determine the presence of subsurface clathrates.
“Clathrates” generally refer to non-stoichiometric metastable substances in which lattice structures composed of first molecular components (host molecules) trap or encage one or more other molecular components (guest molecules) in what resembles a crystal-like structure. Clathrates are sometimes referred to as inclusion compounds, hydrates, gas hydrates, methane hydrates, natural gas hydrates, C02 hydrates and the like.
In the field of hydrocarbon exploration and development, clathrates are of particular interest. For example, clathrates exist in which water host molecule lattices encage one or more types of hydrocarbon guest molecule(s). Such hydrocarbon clathrates occur naturally in environments of relatively low temperature and high pressure where water and hydrocarbon molecules are present, such as in deepwater and permafrost sediments. Clathrates at lower temperatures remain stable at lower pressures, and conversely clathrates at higher temperatures require higher pressures to remain stable.
Traditionally, seismic interpretation based on seismic data is used to identify potential zones where clathrates, such as methane hydrates, accumulate as a drilling hazard. This is typically done in a qualitative sense, by determining areas of high amplitude and/or high impedance in seismic data received from well logs, for example to detect areas having greater material density. This arrangement is acceptable for detecting clathrates as a drilling hazard, because existence and location, rather than density, is of primary concern in that context.
However, in other contexts, mere location of clathrates is insufficient. For example, existing analyses of seismic data from existing well logs do not address the volume of hydrate in place for its potential as a resource. Absent some sense for a volume or saturation of clathrates, it may be difficult to determine if harvesting efforts for such clathrates may prove cost-effective.
As such, improvements in the area of seismic interpretation of well logs to detect clathrates are desirable.
In accordance with the following disclosure, the above and other issues are addressed by the following:
In a first aspect, a method of determining a presence and saturation of clathrates includes identifying a potential zone of clathrates based on observed seismic data, the observed seismic data including an observed signal amplitude at the potential zone of clathrates, and assigning subsurface sediment types within and around the potential zone of clathrates. The method also includes creating one or more lithologic type logs based on the interpreted subsurface sediment types, and creating from each of the one or more lithologic type logs a plurality of synthetic logs including compressional velocity at a plurality of possible clathrate saturation levels. The method further includes matching expected signals from one of the plurality of synthetic logs to the observed signals in the observed seismic data to determine a best-fit match synthetic log to the observed seismic data, thereby determining a likely clathrate saturation level from among the plurality of possible clathrate saturation levels.
In a second aspect, a computer-readable storage medium comprising computer-executable instructions is disclosed which, when executed, cause a computing system to perform a method of determining a presence and saturation of clathrates. The method includes identifying a potential zone of clathrates based on observed seismic data, the observed seismic data including an observed signal amplitude at the potential zone of clathrates, and assigning subsurface sediment types within and around the potential zone of clathrates. The method also includes creating one or more lithologic type logs based on the interpreted subsurface sediment types, and creating from each of the one or more lithologic type logs a plurality of synthetic logs including compressional velocity at a plurality of possible clathrate saturation levels. The method further includes matching expected signals from one of the plurality of synthetic logs to the observed signals in the observed seismic data to determine a best-fit match synthetic log to the observed seismic data, thereby determining a likely clathrate saturation level from among the plurality of possible clathrate saturation levels.
In a third aspect, a system includes a computing system including a programmable circuit and a memory, and computer-executable instructions stored in the memory. The computer-executable instructions are arranged to form a clathrate presence and saturation application program including a seismic data observation component configured to allow location of a potential zone of clathrates based on observed seismic data, the observed seismic data including an observed signal amplitude at the potential zone of clathrates. The program also includes a stratigraphic interpretation component used to assign subsurface sediment types within and around the potential zone of clathrates, and a lithologic type log component configured to generate one or more lithologic type logs based on the interpreted subsurface sediment types. The program further includes a synthetic log generator configured to generate a plurality of synthetic logs including compressional velocity at a plurality of possible clathrate saturation levels from each of the one or more lithologic type logs, and a signal matching component configured to determine a best-fit match synthetic log to the observed seismic data, thereby determining a likely clathrate saturation level from among the plurality of possible clathrate saturation levels.
As briefly described above, embodiments of the present invention are directed to methods and systems for detecting the presence and saturation of clathrates, such as methane hydrates, in a underground, or subsurface, location. In particular, the methods and systems discussed herein provide for differentiation of hydrates from other high reflectivity events, and also quantify the amount of the clathrate that is at the specific location.
It is noted that, in general, the possible zones of clathrates generally will be represented in seismic data as shallow, high reflectivity zones that appear in seismic data, but which do not have the same characteristics, relating to velocity pull-up and reflectivity matching, as other possible anomalies in the seismic data, such as free gas. The methods and systems discussed herein provide for differentiation of hydrates from other high reflectivity events, and also quantify the amount of the clathrate that is at the specific location. This differentiation can help high grade portfolios and identify potential drilling hazards. The identification and quantification of methane hydrate in place allows for identification of commercially-viable saturations of accumulated clathrates, for example for drilling and production.
For the purposes of this disclosure, the term “clathrate” will include any and all types of lattice (host) molecule(s) and any and all types of encaged (guest) molecule(s) in all possible combinations. Clathrates can include, for example, transitions between various clathrate lattice structure types; formation, stable state and dissociation, and the substitution of one or more type(s) of molecule by one or more other type(s) of molecule.
In this example embodiment, the clathrate reservoir 102 is shown in fluid communication with a subsea well 112 which, in turn, is connected to production facility 110 by way of tieback 114. Clathrate reservoir 102 primarily produces a mixture of natural gas and water which is delivered to production facility 110 for separation of natural gas and water, and oil if there are significant amounts of oil contained within the mixture.
It is noted that, in the embodiment shown in
It is noted that the production system 100 shown in
As with the hydrocarbon production system 100 of
Referring now to
The memory 304 can include any of a variety of memory devices, such as using various types of computer-readable or computer storage media. A computer storage medium or computer-readable medium may be any medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device. In the embodiment shown, the memory 304 stores a clathrate presence and saturation determination application 308. The application 308 includes a plurality of components, including a seismic data observation component 310, a stratigraphic interpretation component 312, a lithologic type log generation component 314, a synthetic log generation component 316, and a signal matching component 318.
The seismic data observation component 310 receives seismic data provided to the computing system 300, for example as may be received from a wave generation and detection system 116, 216 of
The stratigraphic interpretation component 312 can be used, after identification of possible zones of clathrate formation, to identify different zones of likely sediment types. For example, in example embodiments, a user can use the stratigraphic interpretation component 312 to trace boundaries between types of sediments, and to assign sediment types to the various subsurface features observed. For example, in some cases, a user may assign a particular region to represent a sand pocket in the subsurface sediment, and a second region to represent shale. In such cases, it is noted that clathrates may form in the sand areas, but will not form within the shale areas. An example of such stratographic interpretation is illustrated in
The synthetic log generation component 316 generates one or more types of “synthetic” logs based on the lithologic type log. The synthetic logs can take a variety of forms. In one possible embodiment, the synthetic logs created using the synthetic log generation component 316 can be compressional velocity logs that can be used to match observed compressional velocities in observed locations where clathrate deposits may exist. In alternative embodiments, the synthetic log generation component 316 can generate a set of logs representing a synthetic well log, including one or more of compressional velocity logs, shear velocity logs, density logs, and porosity logs. In either case, the generated logs are generated such that more than one such log is generated for each of the lithologic type logs. Specifically, a plurality of such logs is created at a variety of different possible clathrate concentrations between 0% and 100%. In some cases, a set of possible concentrations, at 10% intervals are created. In other cases, 20% concentration intervals can be used. Other arrangements are possible as well.
The signal matching component 318 is used to match aspects of a synthetic log to the observed seismic data. This can be done in a variety of ways. In some embodiments, a signal amplitude in an area where the clathrate deposit is suspected is compared between the synthetic log and an associated area in the observed log to determine a best-fit match between one of the logs at a particular concentration and signals in the seismic data in the area of suspected clathrates. For example, a signal amplitude in a compressional velocity log generated from a lithologic type log having a particular concentration (e.g., 60%) is compared to a compressional velocity observed in the seismic data to determine that the signal amplitude in the suspected zone of clathrate concentration has a best fit, for example as compared to a signal amplitude computed for a compressional velocity log representing a 40%, 50%, 70%, or other clathrate concentration.
In alternative embodiments, the signal matching component 318 can use other types of signal attributes to perform this best-fit match, or can use other types of synthetic logs that are comparable to the actual seismic data. For example, both signal amplitude and frequency in and surrounding the suspected zone of clathrate concentration can be matched to locate a best fit concentration when comparing synthetic and actual data. Furthermore, beyond performing this comparison using compressional velocity, other types of generated logs (e.g., shear velocity logs, density logs, and porosity logs) or more than one type of log, could be used to perform this matching process.
It is noted that the best-fit matching can be performed in a variety of ways. In a first embodiment, a velocity pull-up effect is matched between the seismic data and the synthetic logs, representing an amount of pull-up that is observed with a computed pull up occurring in the synthetic logs, in particular in the compressional velocity logs. In a second, alternative embodiment, a reflectivity matching process is performed, comparing reflectivity in the seismic data to reflectivity in observed seismic data. Examples of these matching processes are illustrated in
Referring now to
The method 400 further includes assigning one or more subsurface sediment types within and around the potential zone of clathrates, such as by identifying regions of sand and shale in and around the suspected area, as identified by a user (step 406). A lithologic log can then be created based on the identified subsurface sediment types (step 408).
From the lithologic log created, a plurality of synthetic logs are then created (step 410). As noted above, a variety of types of different synthetic logs can be created at each of a plurality of possible clathrate concentrations, from 0% to 100%. The synthetic logs can include a compressional velocity logs, shear velocity logs, density logs, or porosity logs, as noted above. Once the synthetic logs are created, frequency and amplitudes of features in the synthetic logs can be calculated (step 412), for example in an area near and surrounding the previously-identified possible zone of clathrates. This can include, for example, calculating an amplitude of a velocity pull-up, or calculating an amplitude and frequency of a signal for purposes of reflectivity matching. Based on the calculated amplitude and/or frequency, these “expected” signals are compared to the observed seismic data to determine a best-fit match synthetic log to the observed seismic data (step 414). Once a best-fit match is found, that specific synthetic log is associated with a particular clathrate concentration, which corresponds to an estimated clathrate concentration from among the various possible clathrate concentrations represented by the different synthetic logs.
Referring now to
In the embodiment shown, the user can select the anomaly 504, and can identify a simulated well location 506 along which a synthetic seismic log can be generated, using the systems and methods discussed above. Additionally, the user can define a line 508 denoting an edge of a clathrate stability zone, corresponding to a depth and location where clathrates, and in particular methane hydrates, can be located.
As illustrated in
Referring now to
Analogously, in
Referring to
Referring to
Embodiments of the present disclosure can be implemented as a computer process (method), a computing system, or as an article of manufacture, such as a computer program product or computer readable media. The computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process. Accordingly, embodiments of the present disclosure may be embodied in hardware and/or in software (including firmware, resident software, micro-code, etc.). In other words, embodiments of the present disclosure may take the form of a computer program product on a computer-usable or computer-readable storage medium having computer-usable or computer-readable program code embodied in the medium for use by or in connection with an instruction execution system.
Embodiments of the present disclosure, for example, are described above with reference to block diagrams and/or operational illustrations of methods, systems, and computer program products according to embodiments of the disclosure. The functions/acts noted in the blocks may occur out of the order as shown in any flowchart. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
While certain embodiments of the disclosure have been described, other embodiments may exist. Furthermore, although embodiments of the present disclosure have been described as being associated with data stored in memory and other storage mediums, data can also be stored on or read from other types of computer-readable media. Further, the disclosed methods' stages may be modified in any manner, including by reordering stages and/or inserting or deleting stages, without departing from the overall concept of the present disclosure.
The above specification, examples and data provide a complete description of the manufacture and use of the composition of the invention. Since many embodiments of the invention can be made without departing from the spirit and scope of the invention, the invention resides in the claims hereinafter appended.
