Patent Application
20240263546
The disclosure is in the field of water control in oil and gas production from subterranean wells.
Mature fields contribute about 70% of world's hydrocarbon production with water cut over 80%. According to the American Petroleum Institute (“API”) 2008 data, it is predicted that produced water will increase to 300 million bbl per day worldwide by 2020. Just the Permian Basin has the highest amount of produced water among the major U.S. shale formations, while the Marcellus typically generates the lowest quantity of produced water, according to a Barclays research report, Mar. 22, 2017. In the Permian Basin, the water-to-oil ratio is high: for every barrel of oil produced last year, more than 6.5 barrels of water were produced. The Williston Basin had around 1.1 barrels of water produced for every barrel of oil, while 0.9 barrels of water were produced per one barrel of oil in the Eagle Ford. Although Texas has many disposal wells for Permian's produced water, they may not be sufficient, Barclays report says. According to the Energy Makers Advisory Group in Houston, “Next to profitability and safety, water may well be the next most important topic for an oil company, as it has risen to the forefront over the last five years.”
According to the Food and Agriculture Organization of the United Nations, only 2.5% of the world's water is fresh, and the US, depends on it for nearly 90% of withdrawals for public and industrial use, according to a US Geological Survey (USGS).
There has been a long-felt need for improved systems and methods that are more reliable for the diagnosis of the source of water production in an oil and gas well.
In an aspect of the disclosure, a system for diagnosis of a water source of a water production problem in a well, wherein the system comprises:
Detailed embodiments and examples according to the principles of the principles of the disclosure are provided. However, specific portions or functional details disclosed herein are merely representative for purposes of describing example embodiments. Example embodiments can be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein. Example embodiments are capable of various combinations, modifications, equivalents, and alternatives.
The accompanying figures of the drawing are incorporated into the specification to help illustrate examples according to various embodiments of the disclosure. Like references are used for like elements or features throughout the figures of the drawing. It should be understood that the figures of the drawing are not necessarily to scale.
These figures together with the description explain the general principles of the disclosure. The figures are only for the purpose of illustrating preferred and alternative examples of how the various aspects of the claimed inventions can be made and used and are not to be construed as limiting the claimed inventions to only the illustrated and described examples. Various advantages and features of the various aspects of the present inventions will be apparent from a consideration of the drawing.
In some alternative embodiments, the functions or acts can occur out of the order noted in the figures. For example, two figures of the drawing shown in succession can in fact be executed substantially concurrently or can sometimes be executed in the reverse or order, depending upon the functionality or acts involved.
The disclosure will be described by referring to the general context for the systems and methods and to examples of how they can be made and used.
This disclosure provides a variety of water control solutions, including diagnostic systems and methods. In addition, systems and methods according to this disclosure provide suggestions for water control to treatment application deployment. The systems or methods can reduce water production from hydrocarbon reservoirs. In various embodiments, the systems or methods can also to protect water bearing layers from being produced or contaminated. This can have a favorable environmental impact, especially when freshwater reservoirs can remain undisturbed from interacting with treatment fluids of different salinities.
This integrated approach addresses different water production problems that can occur at various stages in the life of a well, such as near-wellbore, and reservoir-related, or stimulation-related problems, which can be characterized in Table 1.
Such water production problems can occur depending on several factors such as the completions nature, reservoir complexities, drive mechanisms, water oil contacts, and type production scheme implemented. Also, combinations of two or more of such problems can be occurring at the same time, adding a great deal of complexity to the water production scenario and diagnosis; for example, a water coning process may also cause channeling behind casing in cases where there is poor cement integrity.
For example,
Such types of water sources are known in the field; however, the diagnosis of a water source of water production is often difficult.
Apparatus and methods for measuring flow of a fluid mixture in a conduit of a well can be used for determining phase fractions within a fluid mixture flow.
For some embodiments according to this disclosure, a multiphase flowmeter includes an array of spatially distributed pressure sensors configured to determine a velocity of the mixture flow and hence the total flow rate, which is applied with information from a differential pressure meter to calculate the bulk density of the fluid mixture. Further, additional speed of sound information or a water-in-liquid ratio can enable differentiation between the oil and water phases. Appropriate flow algorithms can utilize the phase fraction information with the flow rate of the mixture to find individual flow rates for phases, such as oil, water, and gas or gas and liquid, which can represent a combination of oil and water phases.
Such an apparatus for measuring flow of a fluid mixture in a conduit can include: a pressure sensor array-based meter comprising an array of sensors that detect pressure variations traveling with the fluid mixture; and a water-in-liquid ratio meter configured to perform an infrared optical based spectroscopy analysis of the fluid mixture. The apparatus can additionally include, for example, a differential pressure-based meter configured to detect a differential pressure across a flow nozzle.
Such a method of measuring flow of a fluid mixture in a conduit can include: measuring a velocity in the fluid mixture by sensing along the conduit pressure variations traveling with the fluid mixture; measuring a differential pressure across a fluid flow pressure change inducing section along the conduit; measuring a water-in-liquid ratio of the fluid mixture based on infrared optical spectroscopy analysis of the fluid mixture; calculating a density of the fluid mixture based on the differential pressure and the velocity that are measured; calculating a liquid content of the fluid mixture based on the density that is calculated; and calculating individual oil, water and gas flow rates using the liquid content and the water-in-liquid ratio with the velocity that is measured.
U.S. Pat. No. 7,654,155 issued Feb. 10, 2010, and U.S. Pat. No. 7,938,023 issued May 5, 2011, each having for named inventors Espen S. Johansen, Omer Haldun Unalmis, and John Lievois, each of which patent publications is incorporated herein by reference in its entirety, disclose a suitable flowmeter for use according to this disclosure, including three multi-phase flowmeter elements, that is, venturi, sonar, and infra-red.
Further, U.S. Pat. Nos. 7,607,361, 7,834,312, 7,881,884, 8,039,793, 8,274,041, 8,461,519, 9,002,650, 9,383,476, and 11,448,536, each of which is incorporated by reference herein in its entirety, disclose additional devices and methods and features that can be useful for measuring flow of a fluid mixture in a conduit of a well can be used for determining phase fractions within a fluid mixture flow.
An example of a currently commercially available device capable of flow rate and phase fractions within a fluid mixture flow is FORESITE FLOW™ flowmeter available from Weatherford, which is the business of providing energy services.
If there is any conflict in the usages of a word or term in this disclosure and one or more patent(s) or other documents that are incorporated by reference, the definitions that are consistent with the original material of this disclosure should be adopted in interpreting the original material of this disclosure, and the definitions that are consistent with the document incorporated by reference should be adopted in interpreting the material from that document.
Previously, K. S. Chan, “Water Control Diagnostic Plots,” Society of Petroleum Engineers (SPE 30775), 1995, provided a basic technique of using plots to determine excessive water production mechanisms from reservoirs based on numerical simulation. This work consisted of implementing log-log plots of WOR (water/oil ratio) vs production time, and GOR (gas/oil ratio) vs production time to show several curve responses or trends related to different water production mechanisms. The WOR and GOR derivatives with respect to production time had specific signatures capable of identifying water and gas coning, high permeability layer breakthrough, or near wellbore channeling. In K. S. Chan (SPE 30775),
This approach is based on a production analysis that relies production data for a representative period that needs to capture the different stages of a water coning process, which can occur at an early or late stage in the life of a well depending on the rate of coning, and the production program strategy. Evidently, this analysis has a great deal of uncertainties that may lead to a false diagnosis of the water production problem, and, therefore, a failure of water control strategy. In K. S. Chan (SPE 30775),
Among the greatest challenges to solve water production problems have been the incorrect diagnostic approach, the incorrect type of chemical solution, and the incorrect placement of the chemical solution in the wellbore, near-wellbore, or reservoir area.
Different techniques and methods can be applied to wells to reduce the water production (water cut). Some of these methods include placement of:
Unfortunately, the success rate of water control solutions has been low due to wrong or limited approaches applied most of the time. This is a matter of finding the right “fine-tuned” combination to achieve good results. In fact, an effective conformance solution considers that all factors involved in the water management process should integrate, and work in synchronization with one another. The related factors governing this complex process can include:
One typical example of failed water conformance applications, is when the water source of the water production has not been properly identified, and the conformance fluid is injected in the wrong interval causing severe damage and reduction of permeability to producing zone (causing more harm than benefit). Other cases can include successful identification of water source, and ease of placement, however, the conformance fluid is not capable of penetrating the desired area of the formation face due to limitations of physical properties of these fluids, such as viscosity, particle size, density).
For example, when dealing with water coning problems operators frequently try to control water production at a late stage toward when the economic limit of the well has been reached by implementing ineffective fluid selection and poor placing strategies. The fact is that an attempted treatment of this kind of water coning problem has a very low success likelihood, and it narrows down the possible solutions once the cone has grown vertically and has covered the completion as shown in
According to this disclosure, improved analytical systems and methods can be implemented with an analytical tool under MATLAB™ environment capable of integrating reservoir, completion, production, injection, and interventions history data, to diagnose the nature of the water production problem based on data analytics. MATLAB™ by Mathworks is a programming and numeric computing platform commonly used by engineers and scientists to analyze data, develop algorithms, and create models. Of course, other computing platforms or languages can be used.
In various embodiments, once the water source is identified the analytical tool can automatically classify the problem as reservoir related or near wellbore related or stimulation related. Depending upon reservoir properties and key performance indicators (“KPIs”), different fluid system alternatives, pumping design parameters and the depth of penetration (2-4 ft in case of near wellbore issue and 8 ft and above in case of reservoir related water production problem) can be suggested as a possible solution to the problem. Also, the best placement scenario can be recommended and simulated on an in-house wellbore penetration analytical tool equipped with a conformance fluid library that contains the physical properties to each of the existing fluid systems.
All data extracted from every group (e.g., reservoir, completion, production, injection, and interventions history) is analyzed, massaged according to one or more of the following steps, which may be practiced in any practical order:
The steps 1 through 4 is the way the preprocessing of data is handled. The end potential results (knowledge base) has the option to perform multiple sensitivities by including new data, and the model can run new iterations to reflect variability depending on how relevant the newly incorporated data will be as a weighting factor. The user can be presented with several patterns that can be stored in the knowledge base system. Data mining is a valuable step for this water conformance analysis because it will predict trends for typical problems.
Table 6A and Table 6B discussed below illustrates the basic engine that runs based on the data mining. This is a sub-processing matrix (or module) that has accounted for all the well data being used. This module basically relies on correlation analysis, classification, cluster analysis, and prediction of scores.
This is a module that analyzes the produced scores based on data mining to find trends (e.g., correlated water type curves) and perform analysis on potential water production problems. The user will decide which curves, trends or patterns are representative, and at this stage, further sensitivities can be performed if required, as shown in
Wellbore configuration. In this module, the user needs to input the different segments of drilled hole, and casing at specific depths. For example, at a well depth of 5,000 ft, it is required to identify the wellbore diameter, the dimensions of existing casing or liner, and if the casing is cemented or free (no cement). Also, the TOC (top of cement), and the quality cement bond from CBL (cement bond log) survey are desirable inputs, insofar as known, as shown in Table 2.
Production tubulars. In this module, the user specifies the segments (Table 3) of the tubing data, perforation details, WOC (water-oil-contact), location and production log tool (“PLT”) data if available.
Reservoir data and interventions history. In this module the user initializes the reservoir layers, and their properties, and selects which one(s) will be considered for the analysis. There are specific questions (dropdown selection—binary) associated to each of the layers that will help determine existing conditions prone to water production. This data (Table 4) is gathered, cross-checked, and then evaluated.
Historical production data. This module can be used to come up with a water conformance strategy if the well suddenly starts to experience increase in water production. The user needs to input “validated” production data from prior years if available (with minimum requirement of last 6 months) to analyze the stages that the well has undergone, such as choke changes, shut-in, downhole pump change, and wellhead pressure among other parameters. Data massaging and smoothing can also be performed to identify production periods before proceeding to the advanced water diagnostic plots. Table 5 illustrates a sample of the type of basic production data required for this analysis (but not the data over a sufficient period).
This system can also have a real time module that integrates this water conformance analytical tool with the production systems and intelligent continuous water cut meters at the field. This makes it possible for the analytical tool to utilize the production data in real time to continuously create WOR and WOR′ data and plots versus time in real time, for example, as illustrated in
Different plots from the production data can be produced, including for example:
This system can analyze the data with correlation and scoring (or weighting) factors to various types of water sources for water production problems. For example, the data can be summarized regarding a casing leak as presented in Table 6A and then the correlations can be scored (or weighted), if applicable, as illustrated in Table 6B.
This system can then compare the sum of the scoring for the possibility that the water source of a water production problem is a casing leak in comparison to other potential water sources. For example, in this case, the system and method can calculate that of the various possible sources of water production, such as a channel behind pipe, perforations into a water zone, a high permeability streak, water conning, or a casing leak. As per the analysis it indicated that there is 94% probability of casing leak. As will be appreciated by a person of skill in the field, this type of correlation and scoring (weighting) can be done for each type of potential water source of a water production problem and the most likely water source identified with greater confidence than previously possible.
G. Comparison of the Suggest Solution with a Historical Database of Water Conformance Solutions
The analytical tool includes a library of successful case histories along with the type of solution offered. An operator can pull out the information to understand the similarities with the past and predict the solution for the future. See, for example, conformance fluids presented in Table 7.
This analytical tool can store well information, generate a database of the field, and run data analysis to generate multiple sensitivities to identify water production problems, and propose workable solutions to the presented problems. This analytical tool can additionally include a database of solutions offered depending on the reservoir properties and type of water production problem and intensity of water production. The final step can be a comparison of the solution proposed/predicted by this analytical tool with a historical successful case history. This data-analytics-based integrated approach can help operators build trends for water management decision making and field development strategies. Water conformance is a fundamental factor to reservoir management, and planning due to the environmental impact, and extremely high related costs of handling and processing.
This analytical tool includes both real time and historical diagnosis of the water entering the production interval by data integration from different data sources, such as reservoir, production, injection, completion, and history of interventions. Unlike existing screening methods, it does not rely on a single piece of information to determine the problem. This analytical tool can provide a one stop integrated solution for diagnosing the problem and additionally to designing a treatment, where the treatment includes, for example, a chemical solution, placement technique, and depth of penetration. The analytical tool crosschecks the data according to contributing factor matrix to narrow down uncertainty. Commonly this information is scattered and reviewing it separately one by one may not yield a clear signature to identify a water production problem, and its solution. For example, in some cases a bottom aquifer that is protected by a huge seal rock, may not be an indication for water production, and it may not reveal a coning behavior according to the production curves, however, if there is a presence of a conductive natural fracture system associated to the seal rock, this can be a highly likely potential cause for water source, and the solution for each of these problems has a completely different approach.
The initial step is to capture the correct information (data mining, that is, asking the right questions) for candidate screening to decide whether the well can have a water reduction benefit or not. The second stage is to determine the water source, and define if solution is workable, and what are the risks associated to this option. Finally, the placement modeling will provide the basic pumping design parameters, depth of penetration, type of chemicals, cross-linking time, and will consider the need of particulate diversion based on the completion and reservoir complexities.
Therefore, the disclosure can be understood by a person of skill in the art to obtain the purposes and advantages mentioned as well as those that are inherent therein.
The various disclosed embodiments are illustrative only, as the disclosure can be modified and practiced in different but equivalent manners apparent to those skilled in the art having the benefit of the teachings herein. It is, therefore, evident that the particular illustrative embodiments disclosed above can be altered or modified and all such variations are considered within the scope of the disclosure.
The various elements or steps according to the disclosed elements or steps can be combined advantageously or practiced together in various combinations or subcombinations of elements or sequences of steps to increase the efficiency and benefits that can be obtained from the disclosure.
It should be understood that one or more of the above and various embodiments can be combined with one or more of the other various embodiments, unless explicitly stated otherwise.
The illustrative disclosure can be practiced in the absence of any element or step that is not specifically disclosed or claimed.
Any particular embodiment of the disclosure that falls within the prior art can be explicitly excluded from any one or more of the claims. Because such embodiments are deemed to be known to one of ordinary skill in the art, they can be excluded even if the exclusion is not set forth explicitly herein.
Any particular embodiment of the disclosure can be explicitly excluded from a particular patent claim, for any reason, whether or not related to the existence of prior art. Where elements are presented as lists, for example, in Markush group format, each subgroup of the elements is also disclosed, and any element or elements can be removed from the claimed group.
Those of ordinary skill in the art will recognize or be able to ascertain using no more than routine experimentation many equivalents to the specific embodiments of this disclosure. Those of ordinary skill in the art will appreciate that various changes and modifications to this description can be made without departing from the spirit or scope of the disclosure.
The description of the specific examples herein does not necessarily point out what an infringement would be but are to provide at least one explanation of how to make and use the disclosure.
The indefinite articles “a” or “an” mean at least one of the noun or noun phrase that the article introduces.
The conjunction “and” (in the sense of a listing or grouping) is open to additional elements or steps unless the context otherwise requires.
“Or” (conjunction) means: (1) (a) indicating an alternative, usually only before the last term of a series: hot or cold; this, that, or the other; (b) indicating the second of two alternatives, the first being preceded by either or whether; or (2) indicating a synonymous or equivalent expression.
For the purposes of disclosure, conjunctions “or” (in the sense of an alternative) and “and” (in the sense of a listing or grouping) can be interpreted first as open and non-limiting to other or additional possibilities, and, interpreted second, as closed and limiting.
The words “comprising,” “containing,” “including,” “having,” “characterized by,” and all grammatical variations thereof are intended to have an open, non-limiting meaning as to any unstated limitations.
Furthermore, no limitations are intended to the details of composition, design, construction, or steps of the disclosure, other than as set forth in a specific claim.
