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Automatic Calibration of Real-Time Computer Models in Intelligent Drilling Control Systems - Results From a North Sea Field Trial
Lohne, Hans Petter (Intl Research Inst of Stavanger) | Gravdal, Jan Einar (Intl Research Inst of Stavanger) | Dvergsnes, Erik Wolden (Intl Research Inst of Stavanger) | Nygaard, Gerhard Haukenes (Intl Research Inst of Stavanger) | Vefring, Erlend Heggelund (Intl Research Inst of Stavanger)
Abstract Many real-time decision support systems for drilling operations, or advanced drilling control systems, are based on computer models calculating wellbore pressure and mechanical forces on the drillstring. Closed loop control systems, for example for Managed Pressure Drilling, or advanced offshore or onshore decision support systems are examples of systems that may involve such real-time calculations. To obtain a high degree of accuracy in these calculations it is crucial that all parameters describing the system are as correct as possible. Uncertain model parameters may be tuned against measurements. Both surface measurements, like standpipe pressure, hook load and torque, and downhole pressure from Measurement While Drilling tool may be used. Recently, a field trial of such a real-time system with advanced computer models has been performed during a drilling operation in the North Sea. An advanced drilling control system were implemented and tested. The control system includes real-time calculation of both hydraulics and mechanical forces. Key model parameters were tuned using different estimation techniques. The presented methodology for calibration of real-time computer models lead to a more accurate estimation of the status of the well flow and the stresses on the drill-string compared to standard methods, which may be crucial for the performance of real-time decision support systems or advanced drilling control systems. The performance of the calibration methods is studied using results from the North Sea drilling operation. Although the presented results are obtained from a conventional drilling operation this methodology has a broad range of applications. Benefits by this approach are seen by more accurate calculations of downhole hydraulics and stress which are of major importance for safety and economic reasons during drilling operations involving real-time decision support systems or advanced drilling control systems. In the near future application of wired pipe technology will supply advanced real-time systems with more reliable downhole measurements and the possibility of distributed sensors. Given the appropriate calibration techniques, this step-changing technology will lead to better accuracy of estimated state and also forward simulations. Introduction When petroleum reserves are found in areas with narrow sub-surface pressure margins, the wells being planned are more challenging to drill. Due to these challenges, the drilling crew requires more information about the well during the actual drilling operation. Information from the process are typically gathered from sensor at the platform level, such as standpipe pump pressure and main pump drilling fluid volume rate. In addition to these topside measurements, there are also Measurement-While-Drilling (MWD) sensors available that collects data from the bottom hole assembly (BHA), giving information about downhole pressure and temperatures. Data from the MWD-system are typically not available in situations with low or zero drilling fluid flow rate, due to the mud pulse telemetry system that require a certain fluid flow rate to be in operation. In addition, data such a downhole pressure measurements are typically transmitted only every 30 second. A new high-speed telemetry system is now commercially available, giving the possibility of accessing the data at a higher rate and with less transmission noise, [1] and [2].
- North America > United States (1.00)
- Europe > United Kingdom > North Sea (0.81)
- Europe > Norway > North Sea (0.81)
- (3 more...)
Automatic Evaluation of Near-Well Formation Flow Interaction during Drilling Operations
Gravdal, Jan Einar (Intl Research Inst of Stavanger) | Lohne, Hans Petter (Intl Research Inst of Stavanger) | Nygaard, Gerhard Haukenes (Intl Research Inst of Stavanger) | Vefring, Erlend Heggelund (Intl Research Inst of Stavanger) | Time, Rune Wiggo (Intl Research Inst of Stavanger)
Abstract Within the next few years wired drill pipe telemetry is expected to revolutionize the ability to measure and transmit downhole pressure, temperature, mechanical forces and formation parameters in real-time during drilling operations. Bandwidth, reliability and availability will improve dramatically and lead to better premises for developing new technology for more advanced drilling methodology. Downhole real-time measurements are expected to be utilized in a broad range of applications compared to today's drilling procedures. Among these are real-time analysis systems, decision support systems or advanced drilling control systems, e.g. for Managed Pressure Drilling or Underbalanced Operations that will be improved and adapted to this new window into the well. The understanding of interaction between the mud column in the well and the near-well formation is of major importance especially in Managed Pressure Drilling, Underbalanced Operations, or in any drilling operations with narrow pressure window. In this paper, improved methodology for better understanding of well flow, and near-well formation interaction based on this step change in availability of downhole measurements is presented. Model based real-time decision support systems and drilling control systems requires advanced calculation modules that calculates well pressures and flow conditions. For drilling operations with narrow pressure margins where influx from the formation or loss to the formation is likely, it is crucial that such hydraulics models give a good approximation of the physical behavior and the state of the well at all time. The models should therefore be calibrated based on available surface and downhole measurements from the drilling operation. Methodology for automatic calibration of advanced well flow models with formation interaction is presented in this paper and results are given. A more comprehensive real-time hydraulics model constantly calibrating itself against available measurements is a better basis for advanced real-time decision support systems or drilling control systems. Especially for challenging wells with narrow pressure window, such as in depleted reservoirs or deep-water wells this methodology can be useful. Introduction The hunt for hydrocarbons from more "inaccessible" reservoirs has automatically driven the drilling technology towards more advanced techniques and equipment. Drilling operations in deep (and ultra deep) water and in formations with low (even negative) pressure margin are no longer showstoppers for the industry in order to find and produce hydrocarbons. Both economical and environmental issues have emphasized the necessity of developing and implementing new technology in an industry that to some extent has been seen as conservative when it comes to application of new methodology and technology. The request for more information from the well and direct access to down hole tools during the drilling operation has enforced the development of the wired drill pipe telemetry system. Bi-directional real-time drill string telemetry at high speed is now available and may be capable of transmitting data of up to 2 Megabits/sec in the near future [1], [2]. High speed bandwidth from sensors down hole during the entire operation (not only when circulating) and two-way communication with down hole tools is expected to revolutionize drilling operations. In addition, wired drill pipe telemetry enables distributed measurement nodes along the drill string. Altogether, this technology will open up for more extensive use of real-time or quasi real-time systems for automation and decision making. In this context the term automation implies adding intelligent software agents into the control systems that handle downhole tools (e.g. rotary steerable) or rig equipment (e.g. mud pumps, draw-works, top drive or chokes) [3], [4].
- Europe > Norway (1.00)
- North America > United States > Texas (0.94)
- Asia (0.93)
Abstract The value of information (VOI) methodology can be used for determining whether further information should be collected before making a decision. Typically, a VOI is calculated on an expected monetary value (EMV) basis by means of a decision tree, and the cost of the information is compared to the VOI to determine whether to undertake further data collection. A majority of VOI studies employ the discrete decision tree approach to VOI evaluation, thus simplifying the problem by reducing the range of the outcomes and the number of uncertainties addressed at the same time. In order to overcome and address the simplifications introduced when performing a discrete VOI evaluation, a Monte Carlo approach founded on Bayesian decision theory can be applied. This increases computational complexity, but allows for a full uncertainty description of range variables such as oil in place (OIP) and can be integrated with quantitative prospect evaluation methods. The Monte Carlo VOI (MCVOI) approach is presented and compared to the discrete decision tree approach by means of an appraisal well decision. In addition, a complete MCVOI workflow is proposed. The paper aims at familiarizing VOI practitioners with the MCVOI approach by explaining how it works and by illuminating its benefits, such as eased expert assessment and getting past discretization of variables that are inherently continuous. The paper also places the VOI approach in a risk management context, thus extending VOI methodology beyond the pure calculation of a VOI number. Introduction One of the most useful features of decision analysis is its ability to distinguish between constructive and wasteful information gathering. VOI analysis evaluates the benefits of collecting additional information prior to making a decision. Such information gathering may be worthwhile if it holds the possibility of changing the decision that would be made without further information. The majority of VOI applications in the oil and gas industry are based on a discrete approach whereby the uncertainties, both the ones we hope to learn about but cannot directly observe, and the information gathering results, are discretized into a finite number, usually 2-3, of degrees.[1] Although this discretization is sufficient in many situations, continuous representations of the uncertainties may be more suitable for others, such as the uncertainty in oil in place (OIP) or the production in a given year. For some combinations of prior probability distributions and likelihood functions, representing the current information and the confidence related to new information, respectively, Bayesian updating of the probabilities (to get the posterior) is straightforward. Conjugate priors are families of distributions that ease the computational burden when used as prior distributions. Given a conjugate prior, there is a set of likelihood functions for which there exist simple formulas for calculating the posterior distribution. Hence, if the analyst believes that one of these conjugate priors and its associated likelihood functions adequately describe the uncertainties, the probability updating part of the VOI analysis is trivial.