METHODS AND SYSTEMS FOR DETERMINING CLATHRATE PRESENCE AND SATURATION USING SIMULATED WELL LOGS

Methods and systems for determining a presence and saturation of clathrates are provided. One 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 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 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 clathrate saturation level from among the plurality of possible clathrate saturation levels.

DETAILED DESCRIPTION

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.

FIG. 1is a schematic drawing of an example embodiment of an offshore or deepwater hydrocarbon production system100. System100includes a clathrate reservoir102disposed beneath sea water104and seafloor106. This clathrate reservoir102produces water and hydrocarbons, primarily natural gas. In the embodiment shown, an offshore platform108supports a production facility110, which is used to at least partially separate liquids, water and/or oil, from natural gas.

In this example embodiment, the clathrate reservoir102is shown in fluid communication with a subsea well112which, in turn, is connected to production facility110by way of tieback114. Clathrate reservoir102primarily produces a mixture of natural gas and water which is delivered to production facility110for 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 inFIG. 1, a wave generation and detection system116can be used prior to installation of the overall hydrocarbon production system100, and can be used to locate the system100at a particular location along the seafloor106. The wave generation and detection system116can be, for example a seismic or other acoustic wave generation system, or other system capable of generating waves that are able to penetrate the sea water104and seafloor106, and to capture reflected waves, and thereby detect differences in the media through which the waves travel based on speed of travel.

It is noted that the production system100shown inFIG. 1is only an exemplary embodiment. Those skilled in the art will appreciate that it is within the scope of the present invention to provide a hydrocarbon production system that combines multiple such clathrate reservoirs and associated wells, or combination of such a clathrate reservoir and associated well with conventional hydrocarbon reservoir and well systems. An example of such a system is illustrated in U.S. Pat. No. 8,232,428, filed Aug. 25, 2008, the disclosure of which is hereby incorporated by reference in its entirety.

FIG. 2is a schematic drawing of another exemplary embodiment of a hydrocarbon production system200which, in this case, is located on land rather than being based offshore. Production system200includes a clathrate reservoir202. Disposed upon a permafrost layer204is an arctic platform206. A production facility208, generally similar to production system110, is located atop arctic platform206. Production facility208is used to separate and process natural gas, oil and water received from the clathrate reservoir202. Production tubing210is used to fluidly convey a mixture of clathrates and water from clathrate reservoir202to arctic platform206and production facility208. The mixture may include, in some cases, a small portion of oil.

As with the hydrocarbon production system100ofFIG. 1, it is noted that in the context of the on-land arrangement ofFIG. 2, a wave generation and detection system216, analogous to system116ofFIG. 1, can be used prior to installation of the overall hydrocarbon production system200, and can be used to locate the system200at a particular location. The wave generation and detection system216can include any of a variety of types of seismic, acoustic, or other system capable of generating waves that are able to penetrate the permafrost layer204, and to capture reflected waves, and thereby detect differences in the media through which the waves travel based on speed of travel. It is noted that, in the example ofFIG. 2, there are likely to be greater variations in densities at shallower depths, based on the comparative uniformity of sea water as compared to variations found in the on-land subsurface sediments. In either case, such data can be captured for use in some embodiments of the present disclosure, as discussed in further depth below.

Referring now toFIG. 3, an example computing system300is illustrated that can be used to determining an expected presence and saturation of clathrates, such as can be used to locate a production system such as those shown inFIGS. 1-2. In general, the computing system300includes a processor302communicatively connected to a memory304via a data bus306. The processor302can be any of a variety of types of programmable circuits capable of executing computer-readable instructions to perform various tasks, such as mathematical and communication tasks.

The memory304can 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 memory304stores a clathrate presence and saturation determination application308. The application308includes a plurality of components, including a seismic data observation component310, a stratigraphic interpretation component312, a lithologic type log generation component314, a synthetic log generation component316, and a signal matching component318.

The seismic data observation component310receives seismic data provided to the computing system300, for example as may be received from a wave generation and detection system116,216ofFIGS. 1-2, above. The seismic data observation component310can be configured, in some embodiments, to present a display of the seismic data and allow a user to view and identify one or more areas to further analyze for potential presence of clathrates (e.g., methane hydrates). For example, an interactive display can present two-dimensional or three-dimensional seismic data to the user, and allow the user to (with or without assistance by the computing system) locate one or more areas where seismic signals experience a high velocity, high impedance event. Such cases generally exhibit a large velocity pull-up, i.e., where the signal appears shallower than in surrounding areas based on faster traversal of the area having greater density. The interactive display can also allow the user to select such areas, and to define a clathrate stability zone, i.e., a location where pressure and temperature are sufficiently high to support clathrate formation. An example of such a display is provided inFIG. 5, below.

The stratigraphic interpretation component312can 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 component312to 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 inFIG. 6, discussed in further detail below. The lithologic type log generation component314generates at least one lithologic type log. Lithologic type logs generally correspond to logs of the various identified types of stone materials, as defined in the stratigraphic interpretation component312.

The synthetic log generation component316generates 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 component316can 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 component316can 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 component318is 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 component318can 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 inFIGS. 9 and 10, discussed in further detail below.

Referring now toFIG. 4, a method400for determining a presence and saturation of clathrates is illustrated, in an example embodiment of the present disclosure. In the embodiment shown, the method400includes receiving seismic data, for example from an area in which clathrate exploration is performed (step402). This can include, for example, capture of seismic data using a wave generation and detection system116,216ofFIGS. 1-2. The method also includes identifying a potential zone of clathrates, such as methane hydrates, in observed seismic data (step404). The observed seismic data can include data that has an observed signal amplitude and frequency at a variety of depths and locations, including within and surrounding the potential zone of clathrates. The potential zone of clathrates can be located, for example at a depth where pressure and temperature are sufficiently high to support clathrate formation, and where anomalous seismic features are observed due to changes in a velocity pull-up or reflectivity of the seismic signal.

The method400further 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 (step406). A lithologic log can then be created based on the identified subsurface sediment types (step408).

From the lithologic log created, a plurality of synthetic logs are then created (step410). 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 (step412), 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 (step414). 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 toFIGS. 5-11, example graphs that can be generated using the systems and methods of the present disclosure are illustrated.FIG. 5illustrates an annotated seismic data graph500illustrating a zone of potential clathrate formation. The graph500includes seismic data502for a particular area. In the embodiment shown, the seismic data502includes a seismic anomaly504, shown as outlined by short lines. The seismic anomaly can be selected using a graphical interface displayed by a computing system having a clathrate presence and saturation determination application308executing thereon.

In the embodiment shown, the user can select the anomaly504, and can identify a simulated well location506along which a synthetic seismic log can be generated, using the systems and methods discussed above. Additionally, the user can define a line508denoting 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 inFIG. 6, a portion600of the seismic data graph500is shown with stratigraphic information labeled thereon, including areas of sand and shale. In the embodiment shown, five separate areas are identified (labeled1-5). These areas correspond to varying areas of sand and shale, and are selected and labeled based on user experience with such stratigraphic formations.

FIG. 7is an example velocity pull-up map700illustrating areas where velocity pull-up occurs in seismic data. The velocity pull-up map can be generated in the general location where the possible zone of clathrate formation, represented by the seismic anomaly504, is shown. The velocity pull-up map illustrates relative velocity pull-up regions, which may be due to either clathrate formation or the existence of shale or some other high-density feature. Based on the velocity pull-up, and based on the areas in which sand is present, it can be assumed that some possible level of clathrates may be present. As illustrated inFIG. 8, an example graph800illustrating compressional velocity relative to depth at a particular subsurface location representing a synthetic well log is shown. The graph800can be, for example, at a site of a possible zone of clathrates. As illustrated in the graph800, a compressional velocity is mapped across a variety of depths of interest, in and around a zone of possible clathrate formation. In the example shown, an area from about 1000 to about 1500 feet below a marine subsurface level is illustrated as having a high compressional velocity. Based on the graph800, a signal amplitude can be detected.

Referring now toFIGS. 9-10, graphs illustrating a matching process, representing a reflectivity matching and a velocity pull-up matching arrangements, respectively, are shown.FIG. 9is an example graph900illustrating comparison between observed and expected signals based on reflectivity matching to determine a presence and saturation of clathrates at a particular subsurface location. The graph900illustrates a process by which an existing seismic data, referred to as data902, is matched to a particular portion of synthetic data, referred to as data904. In particular, an amplitude and frequency of anomalous events in each set of data are compared, and a particular set of synthetic data904is selected that best matches the seismic data902to determine a clathrate saturation in a particular area.

Analogously, inFIG. 10, an example graph1000is shown, illustrating comparison between observed and expected signals based on velocity pull-up matching to determine a presence and saturation of clathrates at a particular subsurface location. The graph1000illustrates various levels of velocity pull-up. At a leftmost section of the graph, little if any pull-up is exhibited, indicating little velocity pull-up. At a rightmost section of the graph, velocity pull-up is illustrated. Various velocity pull-up amounts will generally have different slopes. By matching a slope of velocity pull-up in synthetic data to the velocity pull-up observed in the seismic data, various concentrations of clathrates can be detected.

Referring toFIG. 11, an example portion1100of the seismic data graph500ofFIG. 5having estimated clathrate presence and saturation identified. In the portion1100shown, various concentrations of clathrates are illustrated. In the embodiment shown, the portion1100includes an 80% concentration level1102and a 0% concentration level1104, mapped to various regions within the zone of possible clathrate concentration.

Referring toFIGS. 1-11overall, it is noted that, once clathrate saturations are determined, it can be substantially easier and more effective to prioritize different areas of clathrate deposits for harvesting. Furthermore, and referring to in particular computing systems embodying the methods and systems ofFIGS. 3-4, it is noted that various computing systems can be used to perform the processes disclosed herein. For example, embodiments of the disclosure may be practiced in various types of electrical circuits comprising discrete electronic elements, packaged or integrated electronic chips containing logic gates, a circuit utilizing a microprocessor, or on a single chip containing electronic elements or microprocessors. Embodiments of the disclosure may also be practiced using other technologies capable of performing logical operations such as, for example, AND, OR, and NOT, including but not limited to mechanical, optical, fluidic, and quantum technologies. In addition, aspects of the methods described herein can be practiced within a general purpose computer or in any other circuits or systems.

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.