US20130110474A1

US20130110474A1 - Determining and considering a premium related to petroleum reserves and production characteristics when valuing petroleum production capital projects

Info

Publication number: US20130110474A1
Application number: US13/282,315
Authority: US
Inventors: Nansen G. Saleri; Robert M. Toronyi; Joseph W. Ault; Cromwell D. Wong
Original assignee: QRI GROUP LLC
Current assignee: QRI GROUP LLC
Priority date: 2011-10-26
Filing date: 2011-10-26
Publication date: 2013-05-02
Also published as: US10329881B1

Abstract

Determining a Reservoir Management Factor™ (RMF™ or β) for a petroleum producer provides a novel indicator and metric that is designed for use in quickly assessing the economics of undertaking petroleum production capital projects for the petroleum producer. The RMF™ or β can be determined according to the following equation:

β=sum of regression coefficients=sum of(reserves coefficient,production coefficient)

- wherein,
  - reserves coefficient=the coefficient of the petroleum producer's reserves; and
  - production coefficient=the coefficient of the petroleum producer's production.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

Not Applicable.

BACKGROUND OF THE INVENTION

1. The Field of the Invention
The invention is in the field of petroleum reservoir asset management, more particularly in the field of petroleum project valuation.
2. The Relevant Technology
Petroleum is a critical fuel source and is the life blood of modern society. There is tremendous economic opportunity in finding and extracting petroleum. Due to a variety of technical and geological obstacles, it is typically impossible to recover all of the petroleum contained in a reservoir. With advancing technologies and increasing economic incentive due to higher crude oil prices, the average petroleum reservoir recovery rate can now approach about 35%. While this represents a significant increase in average total petroleum recovery in recent years, it also means that about 65% of the petroleum found in a typical reservoir remains unrecoverable from an economic and/or technical standpoint.
Given the high cost of exploration, dwindling opportunities to find new petroleum reservoirs, and the rising cost of petroleum as a commodity, there currently exists a tremendous economic opportunity for organizations to significantly increase both short-term and long-term production across their petroleum reservoirs. When determining the value (and thus potential profitability) of a new petroleum project, operators typically consider barrels of P1 (proved developed producing) reserves to be created by the project. However, it can be difficult to determine the true value (and thus the potential profitability) of new petroleum projects. For example, with regard to investing in and determining the value of new petroleum projects, operators often fail to consider current production and other available reserves. These difficulties in turn make it difficult to determine when undertaking a new petroleum project is economically feasible. Further, as technology changes, production rates and proven resources can also change. However, without consideration of these and other types of changes, petroleum project valuations can be less accurate.
While the technology may, in fact, exist to increase current production and/or increase total long-term recovery of an organization's petroleum reservoirs, an impediment to implementing an intelligent long-term plan for maximizing current output, extending the life of each reservoir, and increasing total recovery across reservoirs is inadequate knowledge of where to focus the organization's limited resources for optimal production. For example, while a particular reservoir may underperform relative to other reservoirs, which might lead some to neglect further development of the reservoir, the reservoir may, in fact, contain much larger quantities of recoverable petroleum but be under-producing simply due to poor management. Furthermore, organizations may waste resources developing some reservoirs, in which the production gains achieved are disproportionately small compared to the developmental resources expended. The inability to properly diagnose on which reservoirs to focus further development and resources, and to implement an intelligent recovery plan can result in diminished short-term productivity and long-term recovery across the organization's petroleum reservoirs.
In general, those who operate production facilities typically focus on oil well maintenance at an individual reservoir level, and may even implement the latest technologies for maximizing well output at the reservoir. They fail, however, to understand the total picture of health and longevity of the reservoir, and how the reservoir performs relative to other reservoirs, both on a short-term and on a long-term basis. These difficulties can lead to inaccurate valuations of petroleum projects. For example, assessing a new project, such as, drilling a new well, without considering an operator's overall production and other available reserves can reduce the accuracy of economic indicators with respect to the new project.

BRIEF SUMMARY OF THE INVENTION

The present invention relates to valuing petroleum projects and more particularly to methods, systems, and computer program products for determining and considering a premium related to petroleum reservoir reserve and production characteristics when valuing petroleum projects. The concept may euphemistically be called Reservoir Management Factor™ (RMF™). RMF™ is systematic methodology for accurately determining a premium related to the value of a petroleum project (e.g., drilling a new well or increasing productivity of an existing well).
Determining the Reservoir Management Factor™ (RMF™) is a powerful method for quickly estimating a premium related to the value of a petroleum project that takes into consideration an operator's existing production and capacity reserves. The types of petroleum projects that can be valued include drilling additional wells, stimulating existing wells, and increasing reservoir contact of existing wells. The RMF™ enables engineers, managers, and investors to efficiently and accurately estimate economic feasibility of implementing certain types of capital projects.
In contrast to conventional methods in which only the present value of a petroleum production project is determined, the present invention considers both petroleum production over time and the increase in inventory (petroleum reserves) as a result of implementation of the project. This permits a producer to determine the value of, and more intelligently choose from among, different projects. In general, the RMF™ for a petroleum producer is related to a coefficient of reserves and to a coefficient of production for the petroleum producer. A RMF™ can be an absolute value derived from a multivariable correlation. In some embodiments, the RMF™ is calculated from the sum of an operator's coefficient of reserves plus the operator's coefficient of production.
In general, the dollars per barrel dimensioned RMF™ or β for a petroleum producer can be defined by the following equation:
β=Absolute Value(Coefficient of Reserves+Coefficient of Production)
where,

- Coefficient of Reserves and Coefficient of Production are derived from multivariable correlation to reflect a market value premium if the petroleum production was public

Thus in general, the dollars per barrel dimensioned RMF™ or β is based on reserves and production numbers, which can be calculated and/or can be accessed from corporate documents, such as, for example, 10K filings. Through statistical analysis, a high correlation between production rate, reserves, and market capitalization has been determined to exist.
A more detailed description of how to determine a market value premium for a petroleum producer will be described hereafter. An RMF™ or β can also be used to determine the true value of a capital project. For example, in some embodiments an RMF™ or β is utilized in further calculations to determine a True Value Index™ (TVI™) for a capital project. Additional details regarding the True Value Index™ (TVI™) will also be described hereafter.
The Reservoir Management Factor™ (RMF™) is an indicator or metric designed to quickly access the economic feasibility of undertaking a new capital project related to extracting petroleum from a petroleum reservoir. Embodiments of the invention provide management, engineers and investors with an effective new tool to identify opportunities to extract petroleum reserves with well-recognized financial benefits to involved parties. Notwithstanding its simplicity, indeed as a result of its simplified methodology, the present invention provides a revolutionary new tool that can accurately and efficiently assess the economic feasibility of a capital project which, in turn, permits interested parties to devise more effective and intelligent strategies for implementing petroleum extraction.
The Reservoir Management Factor™ (RMF™) can advantageously be used as part of a more comprehensive reservoir evaluation system and methodology known as Reservoir Competency Asymmetric Assessment™ (or RCAA™), which is discussed more fully below in the Detailed Description.
These and other advantages and features of the present invention will become more fully apparent from the following description and appended claims, or may be learned by the practice of the invention as set forth hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

To further clarify the above and other advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It is appreciated that these drawings depict only illustrated embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:

FIG. 1 schematically illustrates exemplary computer-implemented or controlled architecture that can be used to gather, analyze and/or display data gathered from and about a petroleum reservoir;

FIG. 2 is a flow diagram that illustrates exemplary acts for determining a Reservoir Management Factor™ (RMF™) for a petroleum producer;

FIG. 3A is a scatter plot that illustrates a correlation between market capitalization and production;

FIG. 3B is a scatter plot that illustrates a correlation between market capitalization and reserves;

FIG. 4 is a chart illustrating regression coefficients for reserves and production; and

FIG. 5 is a flow diagram that illustrates exemplary acts for determining a True Value Index™ (TVI™) for a capital project related to petroleum production.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

I. Introduction

Embodiments of the invention relate to the determination of a Reservoir Management Factor™ (RMF™) for a petroleum producer used when valuing capital projects related to extraction of petroleum from a reservoir. The Reservoir Management Factor™ (RMF™) is a novel indicator and metric that is designed to quickly and accurately assess the economic feasibility of undertaking a petroleum related project, such as, for example, drilling one or more additional wells, stimulating one or more existing wells, and/or increasing reservoir contact of one or more existing wells. Embodiments of the invention provide management, engineers and investors with an effective tool to identify opportunities to increase production of a petroleum reservoir with well-recognized financial benefits to involved parties.
The Reservoir Management Factor™ (RMF™) can be used in conjunction with, and as an important component of, a larger, more comprehensive system for assessing petroleum reservoir competency. One example of a larger, more comprehensive system developed by the inventors is known as Reservoir Competency Asymmetric Assessment™ (or RCAA™), a description of which is set forth in U.S. Pat. No. 7,963,327, issued Jun. 21, 2011, and entitled “METHOD FOR DYNAMICALLY ASSESSING PETROLEUM RESERVOIR COMPETENCY AND INCREASING PRODUCTION AND RECOVERY THROUGH ASYMMETRIC ANALYSIS OF PERFORMANCE METRICS,” which is incorporated herein in its entirety by reference.
By way of background, RCAA™ includes several closely interrelated sub-methods or modules that are employed in concert and sequentially. These methods or modules can be used in forming metrics and indicators regarding petroleum reserves that are used as part of the RMF™, and knowledge gained as part of a RMF™ can be further applied to an iterative application of the RCAA™ of the petroleum reserves. The methods or modules are (i) analyzing and diagnosing the specific and unique features of a reservoir (i.e., its “DNA”) using targeted metrics, of which the Reservoir Management Factor™ (RMF™) can be added or modified so as to function as one of the components, (ii) designing a recovery plan for maximizing or increasing current production and ultimate recovery (e.g., increasing recoverable petroleum reserves) from the petroleum reservoir, (iii) implementing the recovery plan so as to increase current production and ultimate recovery of petroleum from the reservoir, and (iv) monitoring or tracking the performance of the petroleum reservoir using targeted metrics and making adjustments to production parameters, as necessary, to maintain desired productivity and recovery.
RCAA™ and RMF™ each rely on intense knowledge gathering techniques, which can include taking direct measurements of the physics, geology, and other unique conditions and aspects of the reservoir and, where applicable, considering the type, number, location and efficacy of any wells that are servicing, or otherwise associated with, the reservoir (e.g., producing wells, dead wells, and observation wells), analyzing the present condition or state of the reservoir using asymmetric weighting of different metrics, and prognosticating future production, recovery and other variables based on a comprehensive understanding of the specific reservoir DNA coupled with the asymmetric weighting and analysis of the data. In some cases, the gathered information may relate to measurements and data generated by others (e.g., the reservoir manager).
In general, RCAA™ is an assessment process which guides both the planning and implementation phases of petroleum recovery. All hydrocarbon assets carry an individual “DNA” reflective of their subsurface and surface features. RCAA™ is an enabling tool for developing and applying extraction methods that are optimally designed to the specifications of individual hydrocarbon reservoirs. Its main value is assisting in the realization of incremental barrels of reserves and production over and above levels being achieved using standard industry techniques. This, in turn, may reduce long-term capital and operating expenses.
According to one embodiment, implementation of RCAA™ spans six interweaving and interdependent tracks: i) Knowledge Systems; ii) Q6 Surveys; iii) Deep Insight Workshops; iv) Q-Diagnostics; v) Gap Analysis; and vi) Plan of Action. The information gathered from these tracks is integrated using modern knowledge-sharing mediums including web-based systems and communities of practice. While the overall business model of RCAA™ includes both technological and non-technological means for gathering the relevant information, the method cannot be implemented without the use of physical processes and machinery for gathering key information. Moreover, implementing a plan of action involves computerized monitoring of well activity. And enhanced reservoir performance results in a physical transformation of the reservoir itself.
Determining a Reservoir Management Factor™ (RMF™) similarly involves physical processes and machinery for gathering key information. Converting such information, which relates to both the geological characteristics of the reservoir as well as operational attributes of the petroleum recovery plan, into a Reservoir Management Factor™ (RMF™) is a transformation of essentially physical data into a diagnostic determination or score of petroleum reservoirs. To the extent that such transformations of data are carried out using a computer system programmed to determine a Reservoir Management Factor™ (RMF™) from the underlying data, more particularly using a processor and system memory, such a computer system is itself a machine.
Because the subsurface plumbing of the reservoir is not homogeneous, it will often be necessary to statistically weight some data points more than others in order to come up with a more accurate assessment of the reservoir. In some cases, outlier data points may simply be anomalies and can be ignored or minimized. In other cases, outliers that show increased recovery efficiency for one or more specific regions of the reservoir may themselves be the ideal and indicate that extraction techniques used in other, less productive regions of the reservoir may need improvement.
Physical processes that utilize machinery to gather data include, for example, 1) coring to obtain down-hole rock samples (both conventional and special coring), 2) taking down-hole fluid samples of oil, water and gas, 3) measuring initial pressures from radio frequency telemetry or like devices, and 4) determining fluid saturations from well logs (both cased hole and open hole). Moreover, once a plan of action is implemented and production and/or recovery from the reservoir are increased, the reservoir is physically transformed from a lower-producing to a higher-producing asset.
Monitoring the performance of the reservoir before, during and/or after implementation of a plan of action involves the use of a computerized system (i.e., part of a “control room”) that receives, analyzes and displays relevant data (e.g., to and/or between one or more computers networked together and/or interconnected by the internet). Examples of metrics that can be monitored include 1) reservoir pressure and fluid saturations and changes with logging devices, 2) well productivity and drawdown with logging devices, fluid profile in production and injection wells with logging devices, and oil, gas and water production and injection rates. Relevant metrics can be transmitted and displayed to recipients using the internet or other network. Web based systems can share such data.
FIG. 1 illustrates an exemplary computer-implemented monitoring and analysis system 100 that monitors reservoir performance, analyzes information regarding reservoir performance, displays dashboard metrics, and optionally provides for computer-controlled modifications to maintain optimal oil well performance. Monitoring and analysis system 100 includes a main data gathering computer system 102 comprised of one or more computers located near a reservoir and linked to reservoir sensors 104. Each computer typically includes at least one processor and system memory. Computer system 102 may comprise a plurality of networked computers (e.g., each of which is designed to analyze a sub-set of the overall data generated by and received from the sensors 104). Reservoir sensors 104 are typically positioned at producing oil well, and may include both surface and sub-surface sensors. Sensors 104 may also be positioned at water injection wells, observation wells, etc. The data gathered by the sensors 104 can be used to generate performance metrics (e.g., leading and lagging indicators of production and recovery), including those which relate to the determination of the Reservoir Management Factor™ (RMF™). The computer system 102 may therefore include a data analysis module 106 programmed to establish reservoir metrics from the received sensor data. A user interface 108 provides interactivity with a user, including the ability to input data relating to a real displacement efficiency, vertical displacement efficiency, and pore displacement efficiency. Data storage device or system 110 can be used for long term storage of data and metrics generated from the data, including data and metrics relating to the Reservoir Management Factor™ (RMF™).
According to one embodiment, the computer system 102 can provide for at least one of manual or automatic adjustment to production 112 by reservoir production units 114 (e.g., producing oil wells, water injection wells, gas injection wells, heat injectors, and the like, and sub-components thereof). Adjustments might include, for example, changes in volume, pressure, temperature, and/or well bore path (e.g., via closing or opening of well bore branches). The user interface 108 permits manual adjustments to production 112. The computer system 102 may, in addition, include alarm levels or triggers that, when certain conditions are met, provide for automatic adjustments to production 112.
Monitoring system 100 may also include one or more remote computers 120 that permit a user, team of users, or multiple parties to access information generated by main computer system 102. For example, each remote computer 120 may include a dashboard display module 122 that renders and displays dashboards, metrics, or other information relating to reservoir production. Each remote computer 120 may also include a user interface 124 that permits a user to make adjustment to production 112 by reservoir production units 114. Each remote computer 120 may also include a data storage device (not shown).
Individual computer systems within monitoring and analysis system 100 (e.g., main computer system 102 and remote computers 120) can be connected to a network 130, such as, for example, a local area network (“LAN”), a wide area network (“WAN”), or even the Internet. The various components can receive and send data to each other, as well as other components connected to the network. Networked computer systems and computers themselves constitute a “computer system” for purposes of this disclosure.
Networks facilitating communication between computer systems and other electronic devices can utilize any of a wide range of (potentially interoperating) protocols including, but not limited to, the IEEE 802 suite of wireless protocols, Radio Frequency Identification (“RFID”) protocols, ultrasound protocols, infrared protocols, cellular protocols, one-way and two-way wireless paging protocols, Global Positioning System (“GPS”) protocols, wired and wireless broadband protocols, ultra-wideband “mesh” protocols, etc. Accordingly, computer systems and other devices can create message related data and exchange message related data (e.g., Internet Protocol (“IP”) datagrams and other higher layer protocols that utilize IP datagrams, such as, Transmission Control Protocol (“TCP”), Remote Desktop Protocol (“RDP”), Hypertext Transfer Protocol (“HTTP”), Simple Mail Transfer Protocol (“SMTP”), Simple Object Access Protocol (“SOAP”), etc.) over the network.
Computer systems and electronic devices may be configured to utilize protocols that are appropriate based on corresponding computer system and electronic device on functionality. Components within the architecture can be configured to convert between various protocols to facilitate compatible communication. Computer systems and electronic devices may be configured with multiple protocols and use different protocols to implement different functionality. For example, a sensor 104 at an oil well might transmit data via wire connection, infrared or other wireless protocol to a receiver (not shown) interfaced with a computer, which can then forward the data via fast Ethernet to main computer system 102 for processing. Similarly, the reservoir production units 114 can be connected to main computer system 102 and/or remote computers 120 by wire connection or wireless protocol.
Embodiments within the scope of the present invention also include physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer system. Computer-readable media that store computer-executable instructions are computer storage media (devices). Computer-readable media that carry computer-executable instructions are transmission media. Thus, by way of example, and not limitation, embodiments of the invention can comprise at least two distinctly different kinds of computer-readable media: computer storage media (devices) and transmission media.
Computer storage media (devices) includes RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.
A “network” is defined as one or more data links that enable the transport of electronic data between computer systems and/or modules and/or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a transmission medium. Transmissions media can include a network and/or data links which can be used to carry or desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer-readable media.
Further, upon reaching various computer system components, program code means in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to computer storage media (devices) (or vice versa). For example, computer-executable instructions or data structures received over a network or data link can be buffered in RAM within a network interface module (e.g., a “NIC”), and then eventually transferred to computer system RAM and/or to less volatile computer storage media (devices) at a computer system. Thus, it should be understood that computer storage media (devices) can be included in computer system components that also (or even primarily) utilize transmission media.
Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor, cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. The computer executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, or even source code.

Ii. Determining the Reservoir Management Factor™ for a Petroleum Producer

In general, a Reservoir Management Factor™ (RMF™ or β) is a statistically driven value with a high correlation to a petroleum producer's market capitalization that also captures the effect on market value for a capital project. The Reservoir Management Factor™ (RMF™ or β) represents a factor for calculating a premium to the value of any capital petroleum projects undertaken by the petroleum producer. FIG. 2 is a flow diagram that illustrates exemplary acts in a process 200 for determining a Reservoir Management Factor™ (RMF™) for a petroleum producer. Process or sequence 200 includes an act or step 201 of determining or obtaining a coefficient of reserves for the petroleum producer. The process or sequence 200 further includes an act or step 202 of determining or obtaining a coefficient of production for the petroleum producer. The process or sequence 200 further includes an act or step 203 of relating the sum of the coefficient of reserves and the coefficient of production through a multivariable correlation to obtain a Reservoir Management Factor™ (RMF™ or β) for the petroleum producer such as, for example, according to the following equation:
β=sum of regression coefficients=sum of(reserves coefficient,production coefficient)
wherein,

- reserves coefficient=the coefficient of the petroleum producer's reserves; and
- production coefficient=the coefficient of the petroleum producer's production.

Reserves coefficient and production coefficient can determined by using statistical methods on historical data for petroleum producers. In general, there exists a relatively high correlation (e.g., >0.70) between reserves, production, and market capitalization. Reserves and production numbers can be determined from measurement data taken in accordance with sensors 104. Alternatively, at least some reserves and production numbers can be obtained from corporate filings, such as, for example, 10K filings.
FIG. 3A is a scatter plot 300 that illustrates a correlation between market capitalization and production. In general, there is a relatively strong relationship (e.g., >0.70 correlation) between market capitalization and production at any given point in time. For example, scatter plot 300 depicts a 0.773 correlation between market capitalization and production based on a 10 year observation for petroleum producers 301-325.
FIG. 3B is a scatter plot 350 that illustrates a correlation between market capitalization and reserves. In general, there is a relatively strong relationship (e.g., >0.70 correlation) between market capitalization and reserves at any given point in time. For example, scatter plot 350 depicts a 0.90 correlation between market capitalization and reserves based on a 10 year observation for petroleum producers 301-325.
FIG. 4 is a chart 400 illustrating regression coefficients for reserves and production. As depicted, reserves coefficient 401 has a value of $61.30/bbl and production coefficient 402 has a value ($47.17/bbl). Based these values, a Reservoir Management Factor™ (RMF™ or β) for a petroleum producer can be calculated as follows:
β=Sum($61.39/bbl,−$47.17/bbl)=$14.22/bbl
The Reservoir Management Factor™ (RMF™ or β) represents a premium of $14.22/bbl for new reserves to be created by any projects for the petroleum producer. A Reservoir Management Factor™ (RMF™ or β) can be used to determine the true value of a petroleum project. For example, in some embodiments an RMF™ or β is utilized in further calculations to determine a True Value Index™ (TVI™) for a capital project.
FIG. 5 is a flow diagram that illustrates exemplary acts of a process 500 for determining a True Value Index™ (TVI™) for a capital project related to petroleum production, such as, for example, drilling additional wells, stimulating existing wells, and/or increasing reservoir contact of existing wells. Process or sequence 500 includes an act or step 501 of determining or obtaining data relating to a Reservoir Management Factor™ (RMF™) for a petroleum producer (β). The process or sequence 500 further includes an act or step 502 of determining data relating to the barrels of proven reserves to be created by a capital project (Reserves). The process or sequence 500 further includes an act or step 503 of determining or obtaining data relating to a net present value of the capital project (NPV). The process or sequence 500 further includes an act or step 504 of relating the reserve management factor to the barrels of proven reserves and relating the relation of the reserve management factor to the barrels of proven reserves to the net present value, to obtain the True Value Index™ (TVI™) for the capital project, such as, for example, according to the following equation:
TVI=NPV+(β*Reserves)
where,

- NPV=Net present value of a project;
- β=Reservoir Management Factor (RMF™)=absolute value (sum of Coefficient of Reserves and Coefficient of Production) derived from multivariable correlation (i.e., to reflect the market value premium on increased reserves if the producer was public); and
- Reserves=Barrels of proven reserves to be created by the project.

Petroleum reserves can be classified in a variety of different ways. Reserves can refer to quantities of petroleum claimed to be commercially recoverable by application of development projects to known accumulations under defined conditions. Various criteria are to be satisfied for petroleum to be classified as reserves, such as, for example, discovered through one or more exploratory wells, recoverable using existing technology, commercially viable, and remaining in the ground.
Reserves estimates can have inherent uncertainty, for example, depending on the amount of reliable geological and engineering data available and the interpretation of those data. The relative degree of uncertainty can be expressed by dividing reserves into two principal classifications—“proven” (or “proved”) and “unproven” (or “unproved”). Unproven reserves can further be divided into two subcategories—“probable” and “possible”—to indicate the relative degree of uncertainty about their existence. Commonly accepted definitions of these can be based on those approved by the Society of Petroleum Engineers (SPE) and the World Petroleum Council (WPC) in 1997.
Proven reserves are those reserves claimed to have a reasonable certainty (e.g., normally with at least 90% confidence) of being recoverable under existing economic and political conditions, with existing technology. Industry specialists refer to this as P90 (i.e., having a 90% certainty of being produced). Proven reserves are also known in the industry as 1P (or P1). Proven reserves can also be further subdivided into “proven developed” (PD) and “proven undeveloped” (PUD). PD reserves are reserves that can be produced with existing wells and perforations, or from additional reservoirs where minimal additional investment (operating expense) is required. PUD reserves require significant additional capital investment (e.g., drilling new wells) to bring the oil to the surface.
Unproven reserves are based on geological and/or engineering data similar to that used in estimates of proven reserves, but technical, contractual, or regulatory uncertainties preclude such reserves being classified as proven. They are sub-classified as probable and possible. Probable reserves are attributed to known accumulations and claim a 50% confidence level of recovery. Industry specialists refer to them as P50 (i.e., having a 50% certainty of being produced). These reserves are also referred to in the industry as 2P (P2) (proven plus probable).
Possible reserves are attributed to known accumulations that have a lower chance of being recovered than probable reserves. This term is often used for reserves which are claimed to have at least a 10% certainty of being produced (P10). Reasons for classifying reserves as possible include varying interpretations of geology, reserves not producible at commercial rates, uncertainty due to reserve infill (seepage from adjacent areas), and projected reserves based on future recovery methods. They are referred to in the industry as 3P (or P3) (proven plus probable plus possible).
For example, the petroleum producer may be considering a project to create 740,000 barrels of reserves. The Net Present Value (“NPV”) of the project may be $40 million. The True Value Index™ (TVI™) for the project can be calculated as follows:
$\begin{matrix} TVI = $40 MM + ($14 .22 / b bl * 740, 000 barrels) \\ = $40 MM + ($10 .52 MM) \\ = 50.52 MM \end{matrix}$
In short, the present invention provides a simple, yet powerful, diagnostic tool that can be used to quickly and accurately assess the Reservoir Management Factor (RMF™) for a petroleum producer. The Reservoir Management Factor (RMF™) accounts for the impact of petroleum producer's reserves and production on valuing project decisions. The inventiveness of the disclosed methods lies in their simplicity and ease of implementation. Although sophisticated managers and operators of petroleum reservoirs have been assessing capital projects for decades, and there has existed a long-felt need for finding improved and more streamlined methods for assessing opportunities for economically increasing petroleum production, those of skill in the art have overlooked and failed to appreciate the powerful diagnostic power and quick implementation of the methods disclosed herein, which satisfy a long-felt need known in the art but heretofore unsatisfied. Moreover, the accuracy by which one may quickly determine a Reservoir Management Factor (RMF™) for a petroleum producer is, compared to conventional practices, unpredictable and an unexpected result.
The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims

What is claimed is:

1. In a computing system having a processor and system memory and which is configured to receive and analyze data relating petroleum rate production for a petroleum producer and petroleum reserves for the petroleum producer, a method for determining a reservoir management factor for a petroleum producer, comprising:

inputting into the computing system a coefficient of reserves for the petroleum producer;

inputting into the computing system a coefficient of production for the petroleum producer; and

relating the coefficient of reserves and the coefficient of production through a multivariable correlation to obtain the reservoir management factor (β).

2. The method as in claim 1, wherein the coefficient of reserves and coefficient of production are determined at least in part from data included in a 10K filing.

3. The method as in claim 1, further comprising using statistical algorithms to determine the coefficient of production from the historically observed data for a sample set of petroleum producers.

4. The method as in claim 1, further comprising using statistical algorithms to determine the coefficient of reserves from the historically observed data for a sample set of petroleum producers.

5. The method as in claim 1, wherein relating the coefficient of reserves and the coefficient of production through a multivariable correlation comprises relating the sum of the coefficient of reserves and the coefficient of production through a multivariable correlation to obtain the reservoir management factor (β).

6. The method as in claim 5, wherein the reservoir management factor (β) is formulated according to the following equation:

β=coefficient of reserves+coefficient of production

7. The method as recited in claim 1, further comprising determining a true value index (TVI) for a capital project for the petroleum producer, comprising:

inputting into the computing system data relating to the barrels of proven reserves (Reserves) to be created by the capital project;

inputting into the computing system data relating to a net present value (NPV) of the capital project; and

the computing system determining, by relating the reserve management factor to the barrels of proven reserves and relating the relation of the reserve management factor to the barrels of proven reserves to the net present value, the true value index (TVI) for the capital project.

8. A method as in claim 7, wherein the true value index (TVI) is determined according to the following equation:

TVI=NPV+(β*Reserves).

9. A method as in claim 7, further comprising using the true value index (TVI) as part of a method for determining the economical feasibility of the capital project.

10. The method as in claim 7, wherein inputting data relating to the barrels of proven reserves (Reserves) comprises inputting data relating to the barrels of P1 reserves.

11. In a computing system having a processor and system memory and which is configured to receive and analyze data relating petroleum rate production for a petroleum producer and petroleum reserves for the petroleum producer, a method for determining a reservoir management factor (β), comprising

obtaining a coefficient of reserves for the petroleum producer through a multivariable correlation;

obtaining a coefficient of production for the petroleum producer through a multivariable correlation; and

summing the coefficient of reserves and the coefficient of production to obtain the reservoir management factor (β).

12. The method as in claim 11, wherein the coefficient of reserves and coefficient of production are determined from data included in a 10K filing.

13. The method as in claim 11, wherein obtaining a coefficient of reserves for the petroleum producer through a multivariable correlation comprises using statistical algorithms to determine the coefficient of reserves from historically observed data for a sample set of a plurality of petroleum producers.

14. The method as in claim 11, wherein obtaining a coefficient of production for the petroleum producer through a multivariable correlation comprises using statistical algorithms to determine the coefficient of production from historically observed data for a sample set of a plurality of petroleum producers.

16. The method as in claim 11, wherein the reservoir management factor (β) is formulated according to the following equation:

β=coefficient of reserves+coefficient of production

17. The method as in claim 11, wherein the reservoir management factor (β) reflects a market premium on increased reserves if the petroleum producer were a publicly traded corporation.

18. The method as in claim 11, wherein the coefficient of reserves and the coefficient of production are regression coefficients.

19. A method for formulating a reservoir management factor (β) for a petroleum producer, comprising:

formulating a coefficient of reserves for the petroleum producer, the coefficient of reserves being determined through multivariable analysis of historically observed data for a sample set of a plurality of petroleum producers;

formulating a coefficient of production for the petroleum producer, the coefficient of production being determined through multivariable analysis of the historically observed data for the sample set of the plurality of petroleum producers; and

adding the coefficient of reserves to the coefficient of production to obtain the reservoir management factor (β).

20. The method of claim 19, further comprising calculating a true value index (TVI) for a capital project for the petroleum producer, comprising:

accessing data relating to barrels of proven reserves (Reserves) to be created by the capital project;

accessing data relating to a net present value (NPV) of the capital project; and

determining, by relating the reserve management factor to the barrels of proven reserves and relating the relation of the reserve management factor to the barrels of proven reserves to the net present value, the true value index (TVI) for the capital project.