A New Technique for Determining Reservoir Description from Field Performance Data

1970 ◽  
Vol 10 (01) ◽  
pp. 66-74 ◽  
Author(s):  
K.H. Coats ◽  
J.R. Dempsey ◽  
J.H. Henderson
Keyword(s):  
Linear Programming ◽  
Least Squares ◽  
Single Phase ◽  
Field Performance ◽  
Performance Data ◽  
Two Phase ◽  
Reservoir Performance ◽  
Programming Techniques ◽  
Reservoir Description ◽  
Parameter Values

Abstract Reservoir description data largely determine the validity of simulated reservoir performance. This paper presents a method that employs the least paper presents a method that employs the least squares and linear programming techniques to determine a reservoir description from given performance data. The method bandies multiphase performance data. The method bandies multiphase as well as single-phase flow Problems. The description parameters determined by the method may be any physical properties that influence calculated field performance. We believe The technique offers considerably greater efficiency than previously reported techniques. Example applications presented include cases of single-phase gas flow, single-phase oil flow and two-phase gas-water flow. In these particular applications the method gave accurate results with a large range of uncertainty in the reservoir parameters, and with a small number of simulation parameters, and with a small number of simulation runs. Introduction The purpose of reservoir simulation is estimation of future reservoir performance under alternative well configurations or operating conditions. This estimation is increasingly being performed using rather complex, numerical reservoir models. Reservoir description data constitute the bulk of the required input data for these models, and the accuracy of these data largely determine the validity of the calculated results. Thus an obvious problem is the determination of an accurate problem is the determination of an accurate reservoir description. We treat the problem of determining a reservoir description that, when used as input data to a reservoir simulator, results in close agreement between calculated and observed field performance. Field history or performance data are presumed available for some period of time designated the "match period". The available field history may reflect single- or multiphase, multidimensional flow, and the performance data to be matched may be any mix of observed pressures, producing rates, gas-oil and/or water-oil producing ratios. The observed field performance may correspond to a period of depletion and/or injection, or to an period of depletion and/or injection, or to an interference test. Our method for determining a viable reservoir description requires a number of runs using a reservoir simulator, each run using a reservoir description that is random within limits specified by the engineer. We then use a second, small program, that utilizes least squares and linear program, that utilizes least squares and linear programming; techniques, to process the data output programming; techniques, to process the data output from those runs to determine a reservoir description. To illustrate and test this new method, we constructed three example reservoirs experiencing single-phase gas, single-phase oil and two-phase (gas-water) flow, respectively, in two spatial dimensions. Simulator runs were made using a given set of reservoir description parameters. The results of these runs were then treated as "data" and the description parameters considered unknown. The automatic history matching method described in this paper was applied to back out description parameter values from the performance "data". parameter values from the performance "data". The agreement between these values and the true parameter values is given below. parameter values is given below. Reed et al. present an actual field case where the manual approach to matching production history proved prohibitive in both man and machine time. proved prohibitive in both man and machine time. Our least squares, linear programming technique was then used to achieve a satisfactory and economical match of the reservoir performance data. SPEJ P. 66

A Nonlinear Automatic History Matching Technique for Reservoir Simulation Models

1972 ◽  
Vol 12 (06) ◽  
pp. 508-514 ◽  
Author(s):  
L. Kent Thomas ◽  
L.J. Hellums ◽  
G.M. Reheis
Keyword(s):  
Linear Programming ◽  
Least Squares ◽  
Reservoir Simulation ◽  
History Matching ◽  
Nonlinear Problems ◽  
Performance Data ◽  
Automatic History Matching ◽  
Reservoir Simulations ◽  
Highly Nonlinear ◽  
Matching Procedure

Abstract This paper presents a nonlinear optimization technique that automatically varies reservoir parameters to obtain a history match of held parameters to obtain a history match of held performance. The method is based on the classical performance. The method is based on the classical Gauss-Newton least-squares procedure. The range of each parameter is restricted by a box-type constraint and special provisions are included to handle highly nonlinear cases. Any combination of reservoir parameters may be used as the optimization variables and any set or sets of held data may be included in the match. Several history matches are presented, including examples from previous papers for comparison. In each of these examples, the technique presented here resulted in equivalent history matches in as few or fewer simulation runs. Introduction The history matching phase of reservoir simulations usually requires a trial-and-error procedure of adjusting various reservoir parameters procedure of adjusting various reservoir parameters and then calculating field performance. This procedure is continued until an acceptable match procedure is continued until an acceptable match between field and calculated performance has been obtained and can become quite tedious and time consuming, even with a small number of reservoir parameters, because of the interaction between the parameters, because of the interaction between the parameters and calculated performance. parameters and calculated performance. Recently various automatic or semiautomatic history-matching techniques have been introduced. Jacquard and Jain presented a technique based on a version of the method of steepest descent. They did not consider their method to be fully operational, however, due to the lack of experience with convergence. Jahns presented a method based on the Gauss-Newton equation with a stepwise solution for speeding convergence; but his procedure still required a large number of reservoir simulations to proceed to a solution. Coats et al. presented a proceed to a solution. Coats et al. presented a workable automatic history-matching procedure based on least-squares and linear programming. The method presented by Slater and Durrer is based on a gradient method and linear programming. In their paper they mention the difficulty of choosing a step paper they mention the difficulty of choosing a step size for their gradient method, especially for problems involving low values of porosity and problems involving low values of porosity and permeability. They also point out the need for a permeability. They also point out the need for a fairly small range on their reservoir description parameters for highly nonlinear problems. Thus, parameters for highly nonlinear problems. Thus, work in this area to date has resulted either in techniques based on a linear parameter-error dependence or in nonlinear techniques which require a considerable number of simulation runs. The method presented here is a nonlinear algorithm that will match both linear and nonlinear systems in a reasonable number of simulations. HISTORY MATCHING In a reservoir simulation, various performance data for the field, such as well pressures, gas-oil ratios, and water-oil ratios, are used as the basis for the match. During the matching of these performance data certain reservoir and fluid performance data certain reservoir and fluid parameters are assumed to be known while other parameters are assumed to be known while other less reliable data, forming the set (x1, x2...xn), are varied to achieve a match. The objective of the history-matching procedure presented in this paper is to minimize, in a presented in this paper is to minimize, in a least-squares sense, the error between the set of observed and calculated performance data, Fk(x1, x2... xn). SPEJ P. 508

PREDICTION OF RESERVES AND PRODUCTION PERFORMANCE BY SIMULATION: HALIBUT FIELD

1977 ◽  
Vol 17 (1) ◽  
pp. 114
Author(s):  
F. Taylor
Keyword(s):  
Field Performance ◽  
Production Performance ◽  
Core Material ◽  
Well Testing ◽  
Two Phase ◽  
Water Contact ◽  
History Match ◽  
Actual Performance ◽  
Reservoir Performance ◽  
Artificial Lift

Production from Halibut began in 1970 and after seven years 44.7 megatonnes (354 million barrels) of oil have been produced from initial Halibut reserves estimated at 82.1 megatonnes (653 million barrels). Thus the field is 54% depleted and approaching the point where oil production rates will start to decline rapidly due to increasing production of formation water. The accurate prediction of this decline point in time is of critical importance in scheduling the installation of artificial lift facilities. As a result of a 1974 reservoir engineering study, which formed part of the basis for a 53% increase in estimated Halibut reserves, predictions of near term performance have proved to be reasonably accurate and substantiated a decision in 1974 to program installation of artificial lift facilities for a 1978 start-up.A significant part of the 1974 study was the comparison of reservoir performance data obtained through regular reservoir surveillance and specialized well testing programs with predictions of reservoir performance from a three-dimensional, two-phase simulation model of the field. Reservoir description parameters used in the model were varied until its performance matched actual history for the period in hand. In achieving a history match, the model was adjusted: firstly, to reflect permeabilities estimated by in situ pressure build-up and pulse tests (these values being more than twice as high as those measured in recovered core material); secondly, to simulate restricted areas of vertical communication as defined by pulse testing between different sand units; and thirdly, to match water contact rises indicated by TDT logging. Once the model was calibrated by this method it was used to predict field performance over the whole life of the field and to schedule and size additional production facility needs.Since completion of the study, two years of additional reservoir behaviour history have become available. Performance predictions made after achieving a satisfactory history match have been in good agreement with actual performance over the past two years and work is well along on facilities design and implementation.

A TEM study of the influence of microstructure on the superplastic behavior of a U-5.8 wt.% Nb alloy

1986 ◽  
Vol 44 ◽  
pp. 568-569
Author(s):  
G. Mackiewicz Ludtka
Keyword(s):  
Grain Size ◽  
Heating Rate ◽  
Phase Field ◽  
Single Phase ◽  
Superplastic Behavior ◽  
Two Phase ◽  
Single Phase Field

Historically, metals exhibit superplasticity only while forming in a two-phase field because a two-phase microstructure helps ensure a fine, stable grain size. In the U-5.8 Nb alloy, superplastici ty exists for up to 2 h in the single phase field (γ1) at 670°C. This is above the equilibrium monotectoid temperature of 647°C. Utilizing dilatometry, the superplastic (SP) U-5.8 Nb alloy requires superheating to 658°C to initiate the α+γ2 → γ1 transformation at a heating rate of 1.5°C/s. Hence, the U-5.8 Nb alloy exhibits an anomolous superplastic behavior.

Measurements of single-phase and two-phase flows in a vertical pipe using ultrasonic pulse Doppler method and ultrasonic time-domain cross-correlation method

2013 ◽  
Vol 35 (3) ◽  
Author(s):  
Tat Thang Nguyen ◽  
Hiroshige Kikura ◽  
Ngoc Hai Duong ◽  
Hideki Murakawa ◽  
Nobuyoshi Tsuzuki
Keyword(s):  
Time Domain ◽  
Cross Correlation ◽  
Single Phase ◽  
Ultrasonic Pulse ◽  
Phase Flow ◽  
Beam Diameter ◽  
Vertical Pipe ◽  
Two Phase ◽  
Ultrasonic Time ◽  
Pulse Doppler

Ultrasonic Velocity Profile (UVP) method for measurement of single-phase and two-phase flow in a vertical pipe has recently been developed in the Laboratory for industrial and Environmental Fluid Dynamics, Institute of Mechanics, VAST. The signal processings of the UVP method include the ultrasonic pulse Doppler method (UDM)and the ultrasonic time-domain cross-correlation (UTDC) method. For two-phase flow, simultaneous measurements of both liquid and gas are enabled by using a multi-wave ultrasonic transducer (multi-wave TDX). The multi-wave TDX is able to emit and receive ultrasound of two different center frequencies of 2 MHz and 8 MHz at the same time and position. 2 MHz frequency with beam diameter 10 mm is exploited for measurement of gas. 8 MHz one with beam diameter 3 mm is used for liquid. Measurements have been carried out for laminar and turbulent single-phase flows and bubbly counter-current two-phase flows in two flow loops using two vertical pipes of 26 mm inner diameter (I.D.) and 50 mm I.D. respectively. Based on the measured results, assessment of each method is clarified. Applicability of each method for different conditions of pipe flow has been tested. Suggestions for application of the two methods have been recommended.

Method for estimating the wells interference using field performance data

2018 ◽  
pp. 64-69 ◽  
Author(s):  
E.V. Yudin ◽  
◽  
A.E. Gubanova ◽  
V.A. Krasnov ◽  
◽  
...  
Keyword(s):  
Field Performance ◽  
Performance Data
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