History Matching and Quantitative Use of 4D Seismic Data for an Improved Reservoir Characterization

Author(s):  
M. Mezghani ◽  
A. Fornel ◽  
V. Langlais ◽  
N. Lucet
2020 ◽  
Author(s):  
Konrad Wojnar ◽  
Jon S?trom ◽  
Tore Felix Munck ◽  
Martha Stunell ◽  
Stig Sviland-Østre ◽  
...  

Abstract The aim of the study was to create an ensemble of equiprobable models that could be used for improving the reservoir management of the Vilje field. Qualitative and quantitative workflows were developed to systematically and efficiently screen, analyze and history match an ensemble of reservoir simulation models to production and 4D seismic data. The goal of developing the workflows is to increase the utilization of data from 4D seismic surveys for reservoir characterization. The qualitative and quantitative workflows are presented, describing their benefits and challenges. The data conditioning produced a set of history matched reservoir models which could be used in the field development decision making process. The proposed workflows allowed for identification of outlying prior and posterior models based on key features where observed data was not covered by the synthetic 4D seismic realizations. As a result, suggestions for a more robust parameterization of the ensemble were made to improve data coverage. The existing history matching workflow efficiently integrated with the quantitative 4D seismic history matching workflow allowing for the conditioning of the reservoir models to production and 4D data. Thus, the predictability of the models was improved. This paper proposes a systematic and efficient workflow using ensemble-based methods to simultaneously screen, analyze and history match production and 4D seismic data. The proposed workflow improves the usability of 4D seismic data for reservoir characterization, and in turn, for the reservoir management and the decision-making processes.


2006 ◽  
Vol 9 (05) ◽  
pp. 502-512 ◽  
Author(s):  
Arne Skorstad ◽  
Odd Kolbjornsen ◽  
Asmund Drottning ◽  
Havar Gjoystdal ◽  
Olaf K. Huseby

Summary Elastic seismic inversion is a tool frequently used in analysis of seismic data. Elastic inversion relies on a simplified seismic model and generally produces 3D cubes for compressional-wave velocity, shear-wave velocity, and density. By applying rock-physics theory, such volumes may be interpreted in terms of lithology and fluid properties. Understanding the robustness of forward and inverse techniques is important when deciding the amount of information carried by seismic data. This paper suggests a simple method to update a reservoir characterization by comparing 4D-seismic data with flow simulations on an existing characterization conditioned on the base-survey data. The ability to use results from a 4D-seismic survey in reservoir characterization depends on several aspects. To investigate this, a loop that performs independent forward seismic modeling and elastic inversion at two time stages has been established. In the workflow, a synthetic reservoir is generated from which data are extracted. The task is to reconstruct the reservoir on the basis of these data. By working on a realistic synthetic reservoir, full knowledge of the reservoir characteristics is achieved. This makes the evaluation of the questions regarding the fundamental dependency between the seismic and petrophysical domains stronger. The synthetic reservoir is an ideal case, where properties are known to an accuracy never achieved in an applied situation. It can therefore be used to investigate the theoretical limitations of the information content in the seismic data. The deviations in water and oil production between the reference and predicted reservoir were significantly decreased by use of 4D-seismic data in addition to the 3D inverted elastic parameters. Introduction It is well known that the information in seismic data is limited by the bandwidth of the seismic signal. 4D seismics give information on the changes between base and monitor surveys and are consequently an important source of information regarding the principal flow in a reservoir. Because of its limited resolution, the presence of a thin thief zone can be observed only as a consequence of flow, and the exact location will not be found directly. This paper addresses the question of how much information there is in the seismic data, and how this information can be used to update the model for petrophysical reservoir parameters. Several methods for incorporating 4D-seismic data in the reservoir-characterization workflow for improving history matching have been proposed earlier. The 4D-seismic data and the corresponding production data are not on the same scale, but they need to be combined. Huang et al. (1997) proposed a simulated annealing method for conditioning these data, while Lumley and Behrens (1997) describe a workflow loop in which the 4D-seismic data are compared with those computed from the reservoir model. Gosselin et al. (2003) give a short overview of the use of 4D-seismic data in reservoir characterization and propose using gradient-based methods for history matching the reservoir model on seismic and production data. Vasco et al. (2004) show that 4D data contain information of large-scale reservoir-permeability variations, and they illustrate this in a Gulf of Mexico example.


2003 ◽  
Vol 9 (1) ◽  
pp. 83-90 ◽  
Author(s):  
M. Lygren ◽  
K. Fagervik ◽  
T.S. Valen ◽  
A. Hetlelid ◽  
G. Berge ◽  
...  

2019 ◽  
Author(s):  
H. Amini ◽  
M. Rodriguez ◽  
D. Wilkinson ◽  
G.R. Gadirova ◽  
C. MacBeth

2014 ◽  
Author(s):  
Gerard J.P. Joosten ◽  
Asli Altintas ◽  
Gijs Van Essen ◽  
Jorn Van Doren ◽  
Paul Gelderblom ◽  
...  

2010 ◽  
Author(s):  
Flavio Dickstein ◽  
Paulo Goldfeld ◽  
Gustavo Pfeiffer ◽  
Elisa Amorim ◽  
Rodrigo dos Santos ◽  
...  

SPE Journal ◽  
2010 ◽  
Vol 15 (04) ◽  
pp. 1077-1088 ◽  
Author(s):  
F.. Sedighi ◽  
K.D.. D. Stephen

Summary Seismic history matching is the process of modifying a reservoir simulation model to reproduce the observed production data in addition to information gained through time-lapse (4D) seismic data. The search for good predictions requires that many models be generated, particularly if there is an interaction between the properties that we change and their effect on the misfit to observed data. In this paper, we introduce a method of improving search efficiency by estimating such interactions and partitioning the set of unknowns into noninteracting subspaces. We use regression analysis to identify the subspaces, which are then searched separately but simultaneously with an adapted version of the quasiglobal stochastic neighborhood algorithm. We have applied this approach to the Schiehallion field, located on the UK continental shelf. The field model, supplied by the operator, contains a large number of barriers that affect flow at different times during production, and their transmissibilities are highly uncertain. We find that we can successfully represent the misfit function as a second-order polynomial dependent on changes in barrier transmissibility. First, this enables us to identify the most important barriers, and, second, we can modify their transmissibilities efficiently by searching subgroups of the parameter space. Once the regression analysis has been performed, we reduce the number of models required to find a good match by an order of magnitude. By using 4D seismic data to condition saturation and pressure changes in history matching effectively, we have gained a greater insight into reservoir behavior and have been able to predict flow more accurately with an efficient inversion tool. We can now determine unswept areas and make better business decisions.


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