EP2222937A2 - An intelligent drilling advisor - Google Patents
An intelligent drilling advisorInfo
- Publication number
- EP2222937A2 EP2222937A2 EP08843835A EP08843835A EP2222937A2 EP 2222937 A2 EP2222937 A2 EP 2222937A2 EP 08843835 A EP08843835 A EP 08843835A EP 08843835 A EP08843835 A EP 08843835A EP 2222937 A2 EP2222937 A2 EP 2222937A2
- Authority
- EP
- European Patent Office
- Prior art keywords
- drilling
- client
- formulations
- data
- software agent
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
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Classifications
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B44/00—Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
Definitions
- This invention is in the field of the drilling of wells, and is more specifically directed to measurement and control systems for use in such drilling.
- the term "expert system” is known in the art as referring to a software system that is designed to emulate a human expert, typically in solving a particular problem or accomplishing a particular task.
- Conventional expert systems commonly operate by creating a "knowledge base” that formalizes some of the information known by human experts in the applicable field, and by codifying some type of formalism by way the information in the knowledge base applicable to a particular situation can be gathered and actions determined.
- Some conventional expert systems are also capable of adaptation, or "learning", from one situation to the next. Expert systems are commonly considered to in the realm of "artificial intelligence”.
- the term “knowledge base” is known in the art to refer to a specialized database for the computerized collection, organization, and retrieval of knowledge, for example in connection with an expert system.
- Autonomous agents are capable of operating on their own, without requiring guidance or direction from a human user, in effect operating proactively; this autonomy often includes the capability of self-termination by an agent once its tasks are complete.
- Cooperative agents are capable of interacting with other agents to communicate data and results, and to coordinate their individual actions within a larger framework.
- Adaptive agents react to their external environment to adapt their behavior in response to input data and calculations or determinations.
- the distributed software agents operating in the overall system including those agents executed at rig clients T, are autonomous, cooperative, adaptive, mobile, and reactive software agents. These agents include goal-directed and persistent agents, cooperative with other agents to the extent of being able to self-organize into a network of agents. The overall function of these agents will be to interact with the drilling environment, and formulations (e.g., rules, heuristics, calibrations) that have been previously developed, in order to intelligently collect, deliver, adapt, and organize information about the drilling operation.
- formulations e.g., rules, heuristics, calibration
- Data access tools 14 operate to request and process data from sensors S for each of the operating drilling rigs W.
- These data access tools 14 include standardized data access tools 14a, which refer software applications required to receive data in various formats (e.g., WITSML, LAS, CSV, WITS format data) via software agents and other such applications.
- standardized data access tools 14a refers to the multiple standardized formats in which these data are imported, rather than referring to any standardization in the tools themselves; rather, as will be apparent from this specification, these standardized data access tools 14a involve new and unique approaches to the receipt and processing of these data.
- drilling applications stack 12 also includes drilling state influencer tools 14b within information integration environment HE interface data received from these various data providing "entities", or sources. It is contemplated that these drilling state influencer tools 14b can also incorporate various data processing operations.
- various logical servers 16 are also included within information integration environment HE, specifically within drilling applications stack 12 embodied within information integration environment HE, and executed by the one or more physical servers 10 at that level.
- logical servers 16 may be realized by server applications being executed on individual physical server computers 10, or as distributed server applications operating on one or more physical server computers 10; it is contemplated that those skilled in the art having reference to this description will be able to readily implement these and other logical servers that are useful in realizing information integration environment HE according to the preferred embodiment of the invention.
- Expert tools server 16b also operating as part of information integration environment HE, configures and instantiates software agents that acquire data useful for the development of formulations (rules, heuristics, and calibrations), and the updating of previously derived formulations. It is contemplated that these formulations can include "tool kits" of rules, heuristics, and calibrations that are tailored to each of drilling rigs W served by this system, and the fields F in which they are being deployed. In this embodiment of the invention, expert tools server 16b instantiates those agents in response to directives from formulator ADA F, and in a non-real-time basis, considering that the derivation of new or revised formulations is contemplated to not be a real-time exercise.
- agents can be instantiated by expert tools server 16b at such time as convenient for clients T, thus avoiding resource conflicts with essential real-time processes, or with agents instantiated by agent access server 16a.
- the tool kits including the rules, heuristics, and calibrations appropriate for a given rig client T and its well W are then made available to later- configured software agents,
- J Knowledge tools server 16c is another logical server operating within information integration environment HE according to this preferred embodiment of the invention.
- Knowledge tools server 16c provides packages of formulations (rules, heuristics, and calibrations) corresponding to a notional "best well” model for each specific drilling rig W.
- This "best well” model includes rules, heuristics, and calibrations for "how” to drill the optimum well at the location of each specific drilling rig W.
- the optimum well is optimal in a situational sense, such that the applicable rules, heuristics, and calibrations can themselves determine the optimization criteria, for current and expected drilling conditions.
- these recommendations are displayed at rig clients T, and the responses from the driller, for example both "ignore” and “accept” inputs from the driller in response to a recommendation, are also processed and forwarded to formulator ADA_F (along with other measurements) for the derivation of new inferences, and thus updated formulations.
- the "best well" configuration for a given drilling rig W is a virtual ization of information regarding the subsurface at the location of that rig W.
- this virtualized information is arranged as a collection of "metalayers", each metalayer corresponding to an abstraction of a combination of distinct lithological layers, a combination of portions of distinct lithological layers, or a portion of a single distinct lithological layer.
- each of the metalayers will be referred to by way of a "layer name” or other indicator (layer number, offsets, etc.), so as to be correlatable with the drilling measurements acquired by other rigs W within the same or nearby production fields.
- This abstraction of information into metalayers enable this correlation of information among drilling rigs - by referring to a given metalayer by name or some other "tag" or link, specific parameters of the metalayer can be adjusted to be rig-specific, such as the depth at its top and bottom at the specific location of a given drilling rig W.
- the OODA loop operates by considering the awareness of a particular situation (at one or more of the three hierarchical levels), making a decision of an action to take based on that awareness, and then evaluating the result or performance of that action to improve the awareness capability.
- the specific actions performed in an OODA representation of this intelligent system control includes acquiring observations about the current environment, orienting those observations to the system being controlled based on previously gained knowledge, deciding on a course of action, and then acting on the decision, followed by repetition of the observation loop to evaluate the effect of the action taken.
- Information integration environment HE is intended to carry out these OODA steps for the task of drilling a well, with the higher-level comprehension and projection based on formulations created by formulator ADA F, the construction and operation of which will now be described.
- formulator ADA_F may be constructed as multiple computers or servers operating cooperatively, or alternatively as cloud, utility, or autonomic computing. It is contemplated that formulator ADA_F will include substantial memory resources, for example extremely large disk drive systems, for storing large quantities of data over time. As shown in Figure 4, it is contemplated that one such memory source 20 (whether realized by a single dedicated disk drive, or as distributed among multiple disk drives) will store database DB, or another readily-accessible memory arrangement, for receiving and storing data sensed at the drilling rigs W currently in operation, and also data as sensed previously in other drilling rigs.
- database DB or another readily-accessible memory arrangement
- Knowledge base KB may be arranged and operate in the form of a neural net, from the standpoint of its development ⁇ i.e., "training") and operation.
- formulator ADA_F includes WITSML application programming interface (API) 25, by way of which measurement data and the line are received from sensors S via information integration environment HE.
- WITSML application programming interface API
- various "engines” are realized as part of formulator ADA F.
- the term "engine” in this embodiment of the invention refers to hardware and software computational resources that execute particular functions useful in connection with the drilling of oil and gas wells. Certain of those functions will be described in detail below, in connection with the description of the operation of this embodiment of the invention.
- these hardware and software computational resources involved in a particular engine will typically be implemented as one or more software applications or objects, executed by digital logic processing circuitry within the computer system or systems in which formulator AD A F is realized.
- the particular hardware arrangement of formulator ADA_F can vary widely, as discussed above.
- the specific hardware used to implement these functions can also vary widely.
- the same general purpose central processing unit may be used to execute software applications or objects corresponding to each of these functions.
- dedicated processing circuitry may be provided for these functions.
- one or more specific computers may be used to realize a particular engine.
- inference engine 24 is a computational resource, for example a software component executed by programmable processing circuitry within formulator ADA_F, that defines and updates various formulations (rules, heuristics, and calibrations) from information stored in knowledge base KB, as may be applied to measurements and conditions stored in data base DB, and stores those formulations in an accessible form, in knowledge base KB
- Rules engine 26 is a computational resource, again a software component executed by programmable processing circuitry within formulator ADA_F, that selects those formulations that are appropriate for a certain situation, and forwards those rules to information integration environment HE for configuration into software agents that apply those rules at rig clients T.
- rules engine 26 has the capability of inferring logical consequences from a set of "asserted" facts or axioms, which of course correspond to the measurements and conditions stored in database DB.
- algorithms useful in connection with rules engine 26 include a Rete-based algorithm, and a forward chaining rule engine, as commercially available. New or modified rule sets created by inference engine 24 and accessible to rules engine 26 are available for review and verification by a human expert driller, via one of remote administrators RA.
- formulator ADA_F also includes trendologist function 28, which applies specific rules according to which data from sensors S are to be processed, combined, and displayed.
- inference engine 24 generates rules, heuristics, and calibrations that are useful to trendologist function 28, which receives data from sensors S, processes those data for coherence and usefulness, and based on applicable rules for the current drilling situation, arranges data for display at the corresponding rig clients T in a meaningful fashion.
- Agent engine 30 is a computational resource within formulator ADA_F that adds, modifies, deletes, and monitors all software agents that are created within the system. Based upon the results obtained by inference engine 24 as may be verified by a human expert via remote administrators RA, if a new software agent ought to be created, or an existing software agent ought to be modified to be more effective, agent engine 30 is the computing resource that performs that function.
- Drilling state engine 32 is a computational resource within formulator ADA_F in the form of a generic state machine, configurable based on various rules and heuristics as appropriate, to monitor events and to determine drilling "states" (e.g., drilling, sliding, circulating, etc.) for a given drilling rig W, based on the sensed data and knowledge stored in knowledge base KB, according to developed rules and heuristics.
- ADA_F a computational resource within formulator ADA_F in the form of a generic state machine, configurable based on various rules and heuristics as appropriate, to monitor events and to determine drilling "states" (e.g., drilling, sliding, circulating, etc.) for a given drilling rig W, based on the sensed data and knowledge stored in knowledge base KB, according to developed rules and heuristics.
- formulator ADA_F can be implemented by a single installation of hardware, for example deployed at a data center or some other location remote from the drilling sites.
- formulator ADA F can be deployed in a distributed manner, indeed in a manner that is distributed over the same hardware resources as information integration environment HE if desired.
- the distribution of the hardware in the architecture may itself be situationally-aware, with various hardware entities used depending on the sensed and anticipated conditions for the well.
- formulator ADA_F operate as a unitary whole, so that each instance of the information integration environment HE and of rig clients T can benefit from the knowledge gained from all other instances currently operating, and operated in the past.
- the software application may be in the form of a web-based application, in which case the application can reside and be executed remotely.
- Figure 5 represents such a computer readable medium, directly readable or downloadable as the case may be, by way of computer readable medium CRM. It is contemplated that those skilled in the art will be readily able to realize the appropriate computer readable medium and the contents of such a medium by way of which the necessary software application can be installed and implemented on a particular system, based on this description and according to this invention. Operation of the preferred embodiment of the invention
- formulator ADA_F prior to the initiation of a drilling operation at drilling rig Wl at production field Fl, for example, formulator ADA_F will have previously acquired drilling data, including measurements and calculations made by one or more rig clients T at various drilling rigs W in various production fields F. These data will be stored within database DB.
- formulator ADA F have data from the very production field Fl at which drilling is to begin, or from the very equipment of drilling rig Wl itself. Although such data, rules, heuristics, and calibrations will be more accurate if that rig-specific and field-specific information was previously available, drilling can commence at drilling rig Wl based on rules and heuristics that are deemed to be the best fit for that site, or generic drilling rules.
- formulator ADA_F is an adaptive system, the acquisition of new data during the operation of drilling rig Wl in combination with inputs from the driller at rig client Tl and also from human experts at remote administrators RA will result in the development of formulations that will better apply to the current equipment and environment of drilling rig Wl.
- rig client Tl executes one or more software agents instantiated, configured and forwarded to it by information integration environment IIE to assist the driller with control and management of the drilling operation.
- information integration environment IIE information integration environment
- the combination of rig clients T with information integration environment HE and with formulator ADA F implements a three-level "situational awareness" intelligent drilling advisor system, so that attributes of the drilling operation are perceived (i.e., measured and current parameter values evaluated), comprehended (e.g., by determining current "states" of the drilling operation, of the drilling equipment involved, and the subsurface lithology into which the wellbore is being drilled), and projected (e.g,, by making and presenting recommendations for action to the driller).
- This situational awareness is implemented in the rules, heuristics, and calibrations formulated by formulator ADA_F, which are configured as tools by information integration environment HE into software agents selected for particular drilling rigs and clients, and then sent to those rig clients T for execution at the drilling site.
- rig clients T present current measurements, trends and acceptable ranges of those measurements, indications of the current state of the drilling operation, and recommendations for future action, by way of a human machine interface ("HMI") on a visual display, preferably a touchscreen so that the driller's inputs are received by way of the same graphical user interface (GUI).
- HMI human machine interface
- GUI graphical user interface
- Figure 13 illustrates an example of the display from this human machine interface at rig client Tl, at a point in time at which drilling rig
- Wl is idle, having drilled 7690 feet into the earth.
- the human machine interface indicates that the current drilling state is "Not Drilling".
- ADA is a trademark of BP North America Inc., used in connection with its systems and software systems for assisting drilling.
- Wl are received at rig client Tl.
- Another software agent or agents e.g., trend agent A_T and display agent A_D of Figure 5 display the current values of measurements and calculated parameters over time, along with recommended values and a recommended range (shown as the shaded portion within each trend display of Figures 14 and 15).
- trend agent A_T includes various rules, heuristics, and calibrations developed by formulator ADA_F, specifically using its "trendologist" function, to determine a preferred frequency with which the measurements or calculations are derived and displayed, based on the quality of the measurements and other variables; a measure of the reliability of each of these measurements and calculations is also preferably determined.
- Figure 14 illustrates these measurements and calculations as the rate of penetration (ROP), the mechanical specific energy (MSE) corresponding to the energy expended for a given volume of earth removed, bit torque, the weight on bit (WOB), the RPM of the drill string at the rotary table of drilling rig Wl, and the pressure differential (Delta P) between the standpipe pressure and a base setting.
- ROP rate of penetration
- MSE mechanical specific energy
- Wl weight on bit
- Delta P the pressure differential
- the base setting of the pressure differential is derived by the trendologist function 28 of formulator ADA_F at various times and states in the drilling operation, based on sensed measurements such as strokes per minute of the mud pumps, and known mud equipment parameters such as piston diameter, pipe diameter, etc. will affect this base setting.
- the HMI at rig client Tl also indicates recommended actions to be taken ("Set RPM and WOB to Recommended Values" in the example of Figure 14) to optimize the drilling operation, and provides a way for the human driller to enter feedback.
- One or more drilling state agents A_S instantiated and forwarded by information integration environment HE to rig client Tl preferably operates, again according to rules, heuristics, and calibrations derived by formulator ADA F for the particular drilling rig Wl based on its equipment, and the ltthology and location of the site of that drilling rig Wl, to determine whether a drilling dysfunction is occurring based on current and trended measurements and calculations, and if so, what the dysfunction is.
- Figure 15 illustrates such a situation, in which the HMI indicates that a "bit bounce" dysfunction is present; some of the measurements (MSE, Delta P, RPM) are outside of their recommended ranges at this point, and most likely (depending on the rules) were at least partially the basis of the identified dysfunction. A recommendation is also provided to the driller, as before.
- An input mechanism is provided at touchscreen display TDISP, as shown in Figures 13 through 15, by way of which the driller or drilling engineer can choose to "ignore” the displayed recommendation. If this occurs, that "ignore” input will be communicated back to information integration environment IIE and formulator ADA_F, along with measurement data and other information regarding drilling rig W, for incorporation into new and updated rules, heuristics, or calibrations as appropriate. In any event, whatever the action taken by the driller or drilling engineer in response to the recommendation, the system will continue to monitor, communicate, display, and provide recommendations during the drilling operation.
- FIG. 5 illustrates the overall arrangement of software agents and resources associated with those agents, within an example of a system according to this embodiment of the invention.
- Rig client Tl associated with drilling rig Wl in this example, receives signals from sensor S via analog/digital converter 35 and other functions within a data acquisition system (not shown).
- Rig client Tl receives the digital measurement data corresponding to sensor S output via data acquisition application 37 executed at rig client Tl.
- Data acquisition agent Al configured and instantiated by agent access server 16a at information integration environment HE, is executing on rig client Tl, and is forwarding measurement data according to that configuration to information integration environment HE, via agent access server 16a.
- Other software agents are also being executed at rig client Tl, including trend agent A_T for deriving trends of measured data.
- State agent A_S is also executing at rig client Tl, for determining the current drilling state of driUing rig Wl, based on the measurement data and on formulations for determining drilling states.
- Display agent A_D operates to display measurement data, trends of that data, drilling recommendations, current and upcoming drilling state indications, and other information at touchscreen display TDISP of rig client Tl.
- Inputs from the driller (terrestrial drilling) or drilling engineer (offshore drilling) are received by touchscreen display TDISP, and in the case of at least "ignore" inputs responsive to displayed recommendations, are forwarded via function 39 to information integration environment HE, specifically via knowledge tools server 16c therein.
- information integration environment HE includes agent access server 16a.
- Agent access server 16a has access to a collection of "level 1" agents A_l, which include data acquisition agents, trend agents, display agents, and the like that are executable at rig client Tl .
- agent access server 16a can select from among these agents A l, and also from among state agents A_S, depending on the current drilling state and other conditions at drilling rig Wl. This selection, configuring, and instantiation of agents A_l, A_S by agent access server 16a in this situationally aware manner will be described in further detail below relative to Figure 6.
- information integration environment HE also includes expert tools server 16b, described above and which will be further described below.
- Information integration environment IIE processes measurement data received from agent Al at rig client Tl, using data access tools 14a, and forwards these processed data to formulator ADA_F, via data interface 25 (e.g., WITSML API 25, shown in Figure 4).
- Figure 6 illustrates the overall operation of agent-based drilling according to an embodiment of this invention, in connection with multiple drilling rigs W deployed in multiple fields Fl through F4.
- Agent engine 30 identifies software agents that may be useful in connection with the drilling of drilling rigs W in production fields Fl through F4, modifies those agents based on recent updates to formulations (rules, heuristics, and calibrations) by inference engine 24, and monitors those software agents that are in use or become in use within the system. This identification of software agents that may be useful in a particular drilling state is made by agent engine 30, in response to drilling state determinations made by drilling state engine 32.
- agent access server 16a within information integration environment UE selects, configures, and instantiates software agents in a situationally aware manner, for each of the wells W of interest in the multiple production fields Fl through F4.
- the software agents instantiated at rig clients T occur at varying points in time, rather than on a periodic basis; this non-uniform instantiation (and termination) of software agents by agent access server 16a reflects the situational awareness involved in this overall process.
- drilling state engine 32 determines a drilling "state" of each specific drilling rig W, based on measurement data acquired and forwarded to formulator ADA_F from sensors S at that drilling rig W, and based on various formulations, and communicates the deduced drilling state to agent engine 30.
- Agent engine 30 forwards software agents appropriate for that drilling state for that particular drilling rig W to agent access server 16a, if not already at and configured within information integration environment HE.
- agent access server 16a instantiates the indicated software agents at rig client T associated with the drilling rig W of interest.
- drilling rig W can be considered to pass through a variety of drilling states.
- Figure 7 illustrates a state diagram according to which drilling state engine 32 ( Figure 6) can determine the drilling state of drilling rig W.
- the available states are initialization (INIT), adding stand (ADDING), circulating drilling mud (CIRCULATING), rotating the drill string (ROTATING), preparing to add another stand of drill pipe (PREPARING), sliding of the drill string (SLIDING), as well as stopped and paused states.
- the state diagram of Figure 7 illustrates the various transitions that are permissible in this example of the determinations made by drilling state engine 32.
- a transition from state INIT to state ADDING is detected by drilling state engine 32 upon receiving data (e.g., alarms and events from state agents A D executing at rig client Tl) indicating that the elevator of drilling rig W is at the top.
- Transition from state ADDING to state CIRCULATING is deduced upon the detection of stand length, hookload, and pressure measurements being captured, in combination with data indicating that drill string RPM at the top of the drill string is greater than zero, in combination with zero (or negative) weight-on- bit WOB.
- Transition to state SLIDING from CIRCULATING is deduced from positive values of WOB and rate-of-penetration (ROP), in combination with zero drill string RPM.
- the other transitions within the state diagram of Figure 7 in this example are evident from the "Legend" of that Figure, and correspond to knowledge of the behavior of drilling rigs based on various measurements.
- multiple state transition rule sets may be implemented at drilling state engine 32.
- the state transition diagram illustrated in Figure 7 corresponds to the available states for a "running" condition of drilling rig W.
- different state transition rule sets may apply in difference circumstances, for example if the drilling rig is currently being “tripped”, or if a "casing" operation is being performed at the drilling rig, or during particular test sequences such as a blow-out prevention equipment (BOPE) test.
- BOPE blow-out prevention equipment
- drilling state engine 32 deduces a transition to a particular drilling state for each drilling rig W of interest, indicating the same to agent engine 30, which in turn controls agent access server 16a to instantiate or terminate various software agents at the corresponding rig client T for that drilling rig W.
- Agent access server 16a then forwards the appropriate software agents to rig client T over the appropriate physical communications facility (shown as well communication bus 40 in Figure 6), configured as appropriate for the newly- detected state at the corresponding drilling rig W.
- one of the software agents that may be configured, instantiated, and sent to a given rig client Tl for its drilling rig Wl may include data acquisition software agent Al ( Figure 3), by way of which information is acquired from its sensors S.
- Data acquisition software agent Al will be configured for rig client Tl to include those resources applicable to the sensors S that are installed and operational at drilling rig Wl, such configuration being provided by information integration environment HE.
- Agent access server 16a will then send the outfitted software agent to rig client Tl, via well communication bus 40.
- various detailed preconditions are to be satisfied before this agent Al begins its operation at rig client Tl :
- agent access server 16a has forwarded agent Al to rig client Tl;
- agent Al is operating and functioning properly (no execution errors);
- agent Al has obtained the proper security authority, within rig client Tl, to forward data to agent access server 16a.
- software agent Al begins carrying out its assigned task, which in this case is the acquisition of measurement data from sensor S.
- rig client Tl generally executes a resident application to receive data from the data acquisition system, and as determined by that application, writes blocks of data to a file in a memory resource such as a disk drive or flash memory within Tl .
- a sequence of operations by agent Al in acquiring such measurement data may include:
- agent Al detects an "end of file write" to a data file at rig client Tl;
- agent Al "packages" data in the written data file for transmission, e.g., by converting the data to a WITSML format in preparing for transmission of the data to information integration environment HE; • agent Al sends the packaged data file to agent access server 16a via well communication bus 40;
- agent Al receives acknowledgement of valid file receipt from agent access server 16a; • agent Al prepares for a next file, and waits for an "end of file write”.
- Data acquisition software agent Al can remain instantiated at rig client Tl until such time as it is terminated by agent access server 16a in response to a change of state or some other indication from agent engine 30, or upon agent Al terminating itself upon reaching some post-condition event or state.
- more than one data acquisition software agent will typically be active and operating at many rig clients T at any given time, considering that multiple data sources (e.g., sensors S, well parameters WPl and well properties WP2 stored at rig client) will be receiving and providing measurement and other data during drilling operations. Such operation is described above in connection with Figure 3.
- These multiple data acquisition software agents can operate in a coordinated fashion with one another, and with other software agents carrying out other functions, including the trend, display, and drilling state agents being executed at rig clients T, as well as in combination with agents being executed within information integration environment HE and formulator ADA F.
- these data acquisition software agents collect data and information that are used to derive formulations for creating a "best well" model specific to the drilling rig W, and for deducing dynamic transition triggers, based on that model and on the acquired measurement data and information, to provide recommendations to the driller or drilling engineer for achieving that optimum well.
- other agents will be created, configured, and instantiated that perform those functions, examples of which are trend agent A_T, display agent A D, and state agent A S at rig client Tl ( Figure 5).
- These and other software agents operable within the system of this embodiment of the invention preferably have specific agent properties that assist this inter-operation.
- the software agents available and operable within this embodiment of the invention preferably constitute a network of persistent, autonomous, goal-directed, sociable, reactive, non-prescriptive, adaptive, heuristic, distributed, mobile, and self-organizing agents.
- These properties and attributes of software agents will be familiar to those skilled in the art having reference to this specification.
- Adaptive Data Access Tools Data Grinder and Trendologist
- data acquisition software agents A l will typically be operating simultaneously to acquire measurement data and other information ⁇ e.g., well parameters WPl, well properties WP2) regarding drilling rig W.
- the various measurement data provided via these multiple data acquisition software agents will necessarily be of varying time frequency, of varying "quality" (i.e., precision or variability), and will have other varying attributes.
- data access tools 14a within information integration environment HE provide the capability of intelligently and adaptively acquiring these data of varying quality and nature from the various data sources and data acquisition agents.
- trendologist function 28 and data grinders 44] through 44 n adaptively process the data acquired by standardized data access tools 14a ( Figure 4).
- FIG 8 illustrates the flow of measurement data and other information within the system of this embodiment of the invention.
- Data sources Sl through Sn correspond to sensors S that provide measurement data to rig client T, or to data stored within rig client T itself (well parameters WPl, well properties WP2, etc.), or other information regarding drilling rig W.
- Data acquisition software agents Al through An are each instantiated and associated with corresponding data sources Sl through Sn, and operate to acquire measurement data or other information from its corresponding data source Sl through Sn, as described above. According to this embodiment of the invention, each of data acquisition agents Al through An forward the acquired data to a corresponding data grinder 44 1 through 44 ⁇ as shown in Figure 8.
- Data grinders 44 are computing resources located within rig client T, and trendologist is a computing resource located within formulator ADA F ( Figure 4).
- Data grinders 44j through 44 n process the measurement data from corresponding data sources Sl through Sn via agents Al through An.
- the processing applied by data grinders 44 is determined by previously-determined formulations (rules, heuristics, and calibrations) stored in knowledge base KB and accessed by rules engine 26, such formulations typically specific to the corresponding data source S, and in combination with other information regarding drilling rig W, including the current drilling state, past measurements, etc.
- An example of a process that is contemplated to be often applied by data grinders 44 is a low-pass filter, such that higher-frequency variations in the signals from data source S are smoothed over time.
- this processing is performed from one to N times on each block or group of measurement data, as determined by repeat function 45.
- This number of repetitions applied by repeat function 45 will vary among the various data sources S, as indicated by the particular rules being enforced by trendologist 28 upon data grinders 44. It is contemplated that the rules applicable to data grinders 44 and repeat function 45 will consider the quality of the data (i.e., the extent of noise in the data, the variance of the data, the presence and frequency of outliers, and the like), the frequency of the data (i.e., the frequency over time at which measurements are obtained), and the like.
- "reliability" ratings may be computed or otherwise derived from the measurement data by software agents, and used to determine the extent of processing to be applied to the measurement data by data grinders 44, including the number of repetitions.
- the rules may indicate that measurement data from downhole sensors S, which are inherently noisier or otherwise less reliable than sensors at the surface, may require additional filtering and thus a higher number of repetitions through data grinder 44, as compared with the data from the surface sensors.
- Trendologist 28 also includes combining function 46 that combines the processed data from the multiple data sources, and formatting function 48 that formats the processed data, as combined, into a recognizable and processable format for various software agents.
- Combining function 46 refers to various rules, heuristics, and other previously determined formulations to select the various data streams that are to be combined for each of the various purposes and destinations, and optionally weighting the particular data sources in effecting such combination.
- Formatting function 48 arranges the result of the combined processed data into a form that can be immediately utilized by the various destinations, including not only a physical format for the processed and combined data, but also its granularity, smoothness, statistics derived from the various datasets, and the like.
- the selecting and weighting determined by combining function 46 within trendologist 28, and the formatting determined by formatting function 48 within trendologist 28, are applied to data grinders 44 and to other software agents at rig clients T, so that the desired combining and formatting is accomplished.
- Trendologist 28 working in concert with and through data grinders 44, effectively converts the raw input perceived by sensors S into data and information that can be immediately utilized and comprehended by software agents and formulator ADA F.
- Trendologist 28 is automatically and manually scalable, for example by application of rules selected by rules engine 26 for the current situation, to provide the granularity of information needed to provide recommendations to the driller at drilling rig W for adjusting the drilling process.
- the combination of trendologist 28 and data grinders 44 extend the simplistic concepts of WITSML into the creation of a situationally-aware set of data access tools 14a ( Figure 6), accepting any number and manner of drilling perception entities and delivering multiple sets of industry standard, common tool readable, datasets for use within or outside of formulator ADA F.
- the resulting processed and combined data can be rendered complete, compensating for missing data types and incorrect or outlier data, for example for those data outside of previously “agreed” bounds of the downstream agents and formulator processes.
- Inference engine 24 is one destination of these data.
- inference engine 24 is capable of modifying existing formulations, or of creating new formulations and rule sets, including new rule sets that control trendologist 28 itself.
- the new or updated rules are stored in knowledge base KB, and accessible to rules engine 26 for selection according to the current drilling situation.
- Inference engine 24 can also apply new inferences intelligently derived from the newly-received data into knowledge base KB.
- Agent engine 30 can also receive some or all of the processed combined newly- received data from trendologist 28, and can update or configure existing or new software agents accordingly; an agent instantiated by agent engine 30 at formulator ADA_F can also manage the storage of the newly-received data into database DB.
- Drilling state engine 32 can also receive the newly processed measurement data and other information, can identify a current or upcoming drilling state ( Figure 7), and can configure or update state agents A_S accordingly.
- display agent A_D produces one or more recommendations regarding changes or adjustments to make in the drilling process, according to rules, heuristics, and calibrations previously formulated by formulator ADA_F that are configured within display agent A_D; the resulting recommendation, if any, is displayed on touchscreen display TDISP, as described above, the driller or drilling engineer can provide an input ("ignore” or "accept”) via touchscreen display TDISP.
- Trend agent A_T also can receive the processed data from trendologist 28, and derive various trends in the measurements, again according to rules by which trend agent A T was configured by information integration environment HE.
- estimates of measurement data are created, using certain data analyzer parameters selected to create those estimates, for example based upon the quality (e.g., noise energy) of the sensed data, knowledge regarding the model and manufacturer of the sensors (and past history of the quality of such data), other measurements concurrent with the sensed data, the current lithology into which the drilling is taking place at the time of the sensed measurements, and the like. Based on these estimates, such parameters as the current depth, and various current and cumulative parameter values, can be iteratively derived, and used to determine the manner in which the measurements are displayed at the affected rig client T.
- quality e.g., noise energy
- trendologist 28 may calculate data "reliability" values for each measurement, in this manner, and use those reliability measurements in the display of data at rig client T, as well as in decisions and recommendations to be made according to the corresponding formulations.
- Figure 9 illustrates an example of this operation of trendologist 28 and the various software agents and functions within information integration environment HE, in the form of a process flow diagram that creates estimates from various measured parameters, for example the computation of estimates of a parameter along the length of the wellbore, from measurements taken at the surface.
- this operation is being carried out by the network of software agents, as instantiated by agent access server 16a ( Figure 6), and operating in combination with tools 14 ( Figure 4) of information integration environment HE.
- bus management process 52 receives the data from the various sensors S and data acquisition software agents concerned with drilling rig W, to provide measurement data and other information to the overall process.
- depth computation process 56 computes the depth of the wellbore from the various data and information as processed by estimation process 60
- process 62 computes downhole values from received data and information.
- process 64 computes total values for the parameter based on the downhole values from process 62, and from other processing of the data and information by process 60.
- Process 60 then forwards the results to database management process 54 for storage in database DB, and for display at display TDISP of rig client T via display management process 66.
- trendologist 28 also determines a useful scale and granularity for displaying the processed measurement data at touchscreen display TDISP of rig clients T; for example, measurement data that are changing slowly but for which precision is important may be displayed at a magnified scale so that small yet important shifts in the data are visible, while noisy or imprecise measurement data can be shown at a less-magnified scale, or over an expanded time scale.
- Trendologist 28 also receives at least some of the results of the estimates from process 60 as feedback for the data analyzer parameters 58 that it forwards to estimation process 60. Accordingly, the operation of data grinders 44 and trendologist 28 serves to efficiently and intelligently create estimates of various drilling parameters, conditions, and estimated values.
- expert-based drilling is implemented by way of formulator ADA_F operating thorough software agents instantiated by information integration environment HE and executing at rig clients T.
- this expert-based operation of the system of this embodiment of the invention effectively implements situationally aware "experts", in the form of formulations (rules, heuristics, and calibrations) that control the software agents operating in the system.
- the overall result of the expert-based system is to provide the human driller or drilling engineer at the drilling site with recommendations regarding the drilling process, based on recently acquired and processed measurement data and other measurements, and based on inferences and previously generated formulations.
- the expert-based drilling aspect of this invention ensures that the formulations used in connection with the drilling operation are up-to- date, and accurate.
- Figure 10 illustrates the overall operation of expert-based drilling according to an embodiment of this invention, in connection with multiple drilling rigs W deployed in multiple fields Fl through F4.
- inference engine 24 within formulator ADA F determines the frequency and timing at which software agents are to be instantiated and forwarded to the various rig clients T, for purposes of acquiring specific measurement data and other information that may be useful in the updating or creating of formulations (rules, heuristics, and calibrations). This determination may itself be based on rules or heuristics that are developed and updated in response to current conditions and past history.
- expert tools server 16b configures and instantiates the appropriate software agents for gathering the data and information desired by inference engine 24, according to the current formulations for acquiring such data and information.
- expert tools server 16b causes the appropriate one or more of rig clients T to execute those newly instantiated agents, to acquire the measurement data and information required by inference engine 24.
- These data and information may also include any "ignore” inputs issued by the driller or drilling engineer, and the recommendations and situations giving rise to those "ignore” inputs.
- the data acquisition software agents instantiated for this purpose are preferably sufficiently autonomous as to be self- terminating, upon completion of their data acquisition tasks in this instantiation.
- the timing with which these software agents are instantiated at rig clients T, for purposes of new or updated formulations is based on a time sequence, rather than based on situational awareness as in the case described above relative to Figure 6.
- the sources of that data and other information need not be the same sources as used in the determination of current conditions and recommendations, as discussed above relative to Figures 6 through 9.
- the measurement data acquired in connection with the creation and updating of formulations, as shown in Figure 10 are preferably processed, conditioned, and formatted by data access tools 14a, including data grinders 44 ( Figure 8) and trendologist 28 as described above, to facilitate the drawing of inferences and accurate determination of new or updated formulations.
- the processed and conditioned data provided by data access tools 14a in information integration environment IIE are then forwarded to agent engine 30, which in turn forwards the received data and any necessary software agents to inference engine 24.
- Inconsistencies in these rules by the inference engine can be detected by a "consistency enforcer" function within inference engine 24; in the event of a detected inconsistency, inference engine 24 preferably uses its adaptive capability to heuristically derive a potential new rule set. Inference engine 24 operates upon the newly received processed data, in combination with previous formulations and other information stored in knowledge base KB, to create new and updated formulations, including rules and heuristics.
- Another type of formulation that may be created by inference engine 24 in connection with this aspect of the invention is a calibration, by way of which measurement data from one or more sensors S or other data sources may be calibrated with respect to other measurement data, or with respect to inferences or conclusions or recommendations previously reached, thus improving the precision and fidelity of the operation of this system.
- Process 70 which is performed by trendologist 28 in concert with data grinders 44 in response to previously formulated rules selected by rules engine 26 as applicable to the current drilling state and situation, filter, processes, and conditions measurement data RAW_data according to the nature of the measurements, the signal and data quality, and the like, as discussed above.
- Figure 11 illustrates, in connection with process 70, examples of the conditioning applied in this example, including rejection of outlier values, signal conditioning through the application of low-pass filters and other signal processing functions, identification of stable values and trends, and the determination of confidence intervals.
- additional or fewer processes may be applied to measurement data from the various data sources represented within measurement data RAW data.
- the result of process 70 is conditioned dataset COND data.
- Dataset COND data is then characterized by inference engine 24, in process 72, to create inferences from the conditioned data.
- examples of inferences that can be drawn from this characterization include increasing rate-of-penetration, stable weight-on-bit, changes in the slope of Mechanical Specific Energy (MSE), and whether the MSE value is determined or undetermined.
- MSE Mechanical Specific Energy
- Expert-based drilling thus provides a mechanism by which situational ly-aware expert software functions can control software agents that interact among multiple software servers and hardware states to provide recommendations to human drillers in the drilling of a borehole into the earth at a safely maximized drilling rate.
- These expert software functions dispatch the agents, initiate transport of remote memory resources and provide transport of knowledge-base components including formulations (rules, heuristics, and calibrations), according to which a drilling state or drilling recommendation is identified responsive to sensed drilling conditions, in combination with one or more parameters indicated by a lithology model of the location of the drilling rig, and in combination with operational limits on drilling equipment sensor parameters.
- That software experts develop formulations applicable to the drilling she derived from the knowledge base, and transmit those formulations, via an agent, to a drilling advisor client system located at the drilling site.
- That client system including the drilling advisor function is coupled to receive signals from multiple sensors at the drilling site, and is coupled to the servers within the information integration environment to configure and service the software agents.
- the expert-based drilling aspect of this invention enables the overall system to continue to improve the accuracy of its inferences and recommendations, as well as improve the confidence with which those inferences and recommendations are drawn, by periodic or otherwise repeated updating of its rules and heuristics.
- the expertise of the overall system therefore improves over time, and with additional information from each drilling rig W and from other drilling rigs W and production fields F.
- the instantiation or creation of software agents is thus improved with continued operation over time, as these newly instantiated agents can be configured with these updated formulations.
- the system of this embodiment of the invention operates to acquire measurement data and other information from one or more drilling rigs W in one or more production fields F, and to provide information back to the driller or drilling engineer based on that data and information, using previously- derived formulations and information from other wells.
- This information includes recommendations to the driller or drilling engineer regarding the way in which the drilling operation ought to be carried out, including suggested adjustments or changes in the operations carried out at drilling rig W.
- the optimized manner in which the drilling operation is carried out is determined by the system itself, according to a notional "best well" model.
- This best well model is determined, according to this aspect of the invention, using recently and previously acquired measurement data, in combination with determinations of the current drilling state and also in combination with the lithology model and other information acquired or derived extrinsically from the data acquired at drilling rig W itself.
- the creation and updating of formulations according to this notional "best well", and the forwarding of the software agents including formulations corresponding to that best well model, will now be described with reference to Figure 12.
- inference engine 24 creates the formulations
- these formulations created by inference engine 24 are directed toward an optimal notional "best well” model, specific to each drilling rig W in each of the production fields F supported by the system.
- knowledge base KB includes "best well" models created for other drilling rigs W2 through W4 within the same production field FI, as well as models created for other drilling rigs W in the other fields F2 through F4, and perhaps even prior wells in other fields not being currently supported by the system.
- formulations in these previous well models are based on the measurement data and lithology models for the wells at those locations, and recommendations made by the system during the drilling of those models, but also preferably include responses from the driller or drilling engineer in response to those recommendations, as well as verification or adjustments made by off-line human experts by way of remote administrators RA ( Figure 5).
- the best well model for drilling rig Wl will also be based on the measurement data previously acquired during the drilling performed so far at that location (stored in database DB and forwarded by agent engine 30), trends of those measurement data as created by trend agent A_T ( Figure 8) based on trendologist function 28, the drilling state history as determined by drilling state engine 32, and well parameters WPl ( Figure 3) and well properties WP2 stored at rig client Tl for drilling rig Wl.
- An important input from well properties WP2 into inference engine 24 is, of course, the lithology model to which well properties WP2 at rig client Tl link, as this model provides insight into upcoming layers to be encountered in the drilling. "Ignore" inputs issued by the driller or drilling engineer in response to recommendations suggested by the system, and the situations giving rise to those "ignore” inputs, constitute quite useful information in the deriving of a best well model.
- BHA bottom-hole assembly
- limits defined by inference engine as ranges of values within which drilling will be optimized (e.g., based on rate of penetration) within the current layer, or more specifically at the current depth within the current layer.
- the "best well” model includes those rules and heuristics, based for example on the lithology model and current trends in various parameter measurements, that define preventive action to be taken by the drilling rig in advance of unstable or dangerous situations that are due to arise in upcoming layers of the earth. These and other formulations are contemplated to constitute the "package" of formulations corresponding to a "best well” model applied to a given drilling rig W.
- inference engine 24 can be performed according to any one of a wide variety of "artificial intelligence” techniques.
- inference engine 24 may be in the form of a "neural net", in which a collection of inputs are applied to a network of weighted sum functions, to derive a set of outputs.
- neural nets are trained by the application of many training sets of inputs to an initial net, evaluation of the result of the net against a known or desired output value set, and back-propagation through the net to adjust the various weighting factors.
- inference engine 24 may be arranged to implement a more rigorous set of logical rules to implement the best well model in optimizing one or more measurement criteria, with additional information and instances used to modify the logical rules or to create additional rules and logical conditions. Still further in the alternative, inference engine 24 may realize its formulations by use of heuristics, according to which a "softer" result with confidence intervals and the like can be created from a simplification of the overall optimization problem. It is contemplated that those skilled in the art having reference to this specification will be readily able to realize inference engine 24 according to one or more of these or other known artificial intelligence techniques, without undue experimentation.
- inference engine 24 Upon creation of new or updated formulations, inference engine 24 stores the new or updated rules in knowledge base KB, for use by other functions in formulator ADA F such as drilling state engine 32. In addition, these new or updated formulations are then forwarded to knowledge tools server 16c within information integration environment HE. Knowledge tools server 16c then configures software agents with the new or updated formulations corresponding to the "best well" model derived by inference engine 24, as discussed above. These software agents are then instantiated by information integration environment IIE ⁇ e.g., agent access server 16a), and are "pushed" to one or more rig clients T in the supported production fields F to which the new formulation is applicable.
- IIE information integration environment
- display agents A D will generally be the agents that are configured with the new formulations according to the "best well" model, as display agents A_D are the actors that present drilling recommendations to the driller or drilling engineer.
- other agents including trend agents A_T and also data acquisition agents A can also be modified according with the new or updated formulations.
- different data sources may become of interest as a result of the updating of the drilling formulations, in which case new data acquisition software agents A D are instantiated and forwarded to rig client T.
- the software agents configured according to these new or updated formulations are preferably "pushed" to rig clients T in a planned manner, rather than on an immediate basis.
- This available information includes historic, real time, and/or near-real-time depth or time based values in any format of drilling dynamics, earth properties, drilling processes and driller reactions.
- the inference engine operates according to a virtual, heuristic ontology that automatically extends based on the environment sampled, encapsulates rules about the "how” to drill the "best well", "when” to push toward the maximum operating parameters of the drilling rig, and "why" to react ahead of the driller's perception of an impending down hole vibration event.
- the drilling knowledge base KB suggests solutions to problems based on feedback provided by human experts, learns from experience, represents knowledge, instantiates automated reasoning and argumentation for embodying best drilling practices into the "best well”.
- Figure 16 illustrates the overall operation of the system by way of examples of processes carried out by software agents and other components of the system, operating within the multi-level system of rig clients T, information integration environment HE, and formulator ADA F.
- the processes and functions illustrated in Figure 16 are those that are contemplated to be useful in connection with a wide range of situations and events in the drilling operation. However, in the spirit of the immediately previous paragraph, it will be understood that these processes are illustrative examples, and are not intended to limit or otherwise exclude other processes and functions carried out by this system.
- FIG 16 illustrates the acquisition of current real-time sensor information from sensors S at drilling rig Wl, in one of production fields F.
- Rig sensor system 100 at drilling rig Wl refers to an entire set of measurement sensors Sl through Sn, which generate set 101 of isolated analog outputs corresponding to various physical measurements and properties.
- Isolated analog outputs 101 are digitized by analog/digital converter functions 35 in data acquisition systems (not shown) at or near drilling rig Wl, and these digital data are read by data acquisition software agents in process 102 at a desired frequency (e.g., 30 Hz, as shown in Figure 16).
- the particular sensors S from which data are acquired, as well as the frequency of such acquisition etc. are determined in a situationally-aware manner, as described above, based on which particular data acquisition software agents are instantiated and the particular configuration of those agents.
- the sensor data acquired by data acquisition software agents Al through An are forwarded to data grinders 44.
- the initiation of data grinders 44 is illustrated in Figure 16.
- data grinders 44 filter and otherwise process newly acquired measurement data in concert with trendologist 28, in a situationally aware manner according to various rules, heuristics, and calibrations derived for the current drilling state of drilling rig Wl and other parameters; in addition, as described above, the extent of filtering and other processing applied to these data is dependent on which sensor S is providing the measurements, as well as the nature and quality of those measurements.
- These processed measurement data are stored in a drilling data file in database DB.
- drilling state agent A S determines the particular drilling state of drilling rig Wl as described above. If the current drilling state corresponds to a state in which active drilling is being carried out, then process 80 is performed by another instantiated software agent, to generate various drilling data according to the rules, heuristics, and calibrations for which that software agent has been configured. These drilling data are then forwarded to trendologist 28, as shown in Figure 8, for combination with other measurement data and other information, and are forwarded to other software agents and other functions to carry out the processes illustrated in Figure 16.
- the other functions receiving drilling data resulting from process 80 include software agents for computing the rate of penetration in process 82, for computing the current depth of drilling in process 86, for computing bit RPM in process 84, for computing the surface versus downhole pressure in process 88, for computing bit torque in process 90, and for computing weight-on-bit in process 94.
- the software agents carrying out these processes also forward their respective results to trendologist 28, for combination with other data and information, and in some cases to software agents for computing other results in other processes in this overall system.
- These expected drilling parameters include the expected ranges for WOB, ROP, RPM, bit torque, delta pressure, and MSE, as well as the expected limits for WOB, RPM, ROP, and bit torque. These expected drilling parameters are forwarded to driller display agent A_D.
- Rules engine 26 is a computational resource in the form of a software component executed by programmable processing circuitry within formulator ADA F, that selects formulations (rules, heuristics, and calibrations) that are appropriate for a certain situation, and forwards those formulations to information integration environment HE for configuration into software agents that apply those rules at rig clients T.
- measurement data is acquired from sensors S at drilling rig Wl on a substantially continuous basis, for example on the order of thirty data measurements per second from each of the various sensors S, in process 110.
- these data are acquired by data acquisition software agents at rig client Tl, such agents having been instantiated and configured by information integration environment HE.
- data grinders 44 include one or more "circulation" data grinder instances (data grinder 44c in Figure 16) that process and forward measurement data to trendologist 28, for application to rules engine 26 so that software agents can be instantiated and configured to determine the state of drilling mud circulation within drilling rig Wl.
- the particular formulations (rules, heuristics, and calibrations) contemplated to be applicable for evaluation of drilling mud circulation include situationally-aware formulations that are depth, time, and event based, for configuration into the appropriate software agents.
- formulations (rules, heuristics, and calibrations) applied for lost circulation will also be adaptively generated and updated throughout the operation of the system, beginning with models for other drilling rigs and adaptively managed and updated for the current wellbore.
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EP2880260A4 (en) * | 2012-08-01 | 2015-08-12 | Services Petroliers Schlumberger | Assessment, monitoring and control of drilling operations and/or geological-characteristic assessment |
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Also Published As
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WO2009058635A3 (en) | 2009-06-18 |
CA2703376A1 (en) | 2009-05-07 |
CA2703376C (en) | 2015-04-07 |
EA201000680A1 (en) | 2013-05-30 |
EP2222937B1 (en) | 2014-12-31 |
WO2009058635A2 (en) | 2009-05-07 |
BRPI0818815A2 (en) | 2015-04-22 |
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