Integrated Reservoir Model History Matching Workflow: Unlocking Reservoir Opportunities, Onshore Abu Dhabi, UAE

2020 ◽  
Author(s):  
Talla Gueye Setiyo Pamungkas
2013 ◽  
Vol 28 (04) ◽  
pp. 369-375 ◽  
Author(s):  
Oscar Vazquez ◽  
Ross A. McCartney ◽  
Eric Mackay

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

2016 ◽  
Author(s):  
Kevin Michael Torres ◽  
Noor Faisal Al Hashmi ◽  
Ismail Ahmed Al Hosani ◽  
Ali Salem Al Rawahi ◽  
Humberto Parra

SPE Journal ◽  
2006 ◽  
Vol 11 (04) ◽  
pp. 464-479 ◽  
Author(s):  
B. Todd Hoffman ◽  
Jef K. Caers ◽  
Xian-Huan Wen ◽  
Sebastien B. Strebelle

Summary This paper presents an innovative methodology to integrate prior geologic information, well-log data, seismic data, and production data into a consistent 3D reservoir model. Furthermore, the method is applied to a real channel reservoir from the African coast. The methodology relies on the probability-perturbation method (PPM). Perturbing probabilities rather than actual petrophysical properties guarantees that the conceptual geologic model is maintained and that any history-matching-related artifacts are avoided. Creating reservoir models that match all types of data are likely to have more prediction power than methods in which some data are not honored. The first part of the paper reviews the details of the PPM, and the next part of this paper describes the additional work that is required to history-match real reservoirs using this method. Then, a geological description of the reservoir case study is provided, and the procedure to build 3D reservoir models that are only conditioned to the static data is covered. Because of the character of the field, the channels are modeled with a multiple-point geostatistical method. The channel locations are perturbed in a manner such that the oil, water, and gas rates from the reservoir more accurately match the rates observed in the field. Two different geologic scenarios are used, and multiple history-matched models are generated for each scenario. The reservoir has been producing for approximately 5 years, but the models are matched only to the first 3 years of production. Afterward, to check predictive power, the matched models are run for the last 1½ years, and the results compare favorably with the field data. Introduction Reservoir models are constructed to better understand reservoir behavior and to better predict reservoir response. Economic decisions are often based on the predictions from reservoir models; therefore, such predictions need to be as accurate as possible. To achieve this goal, the reservoir model should honor all sources of data, including well-log, seismic, geologic information, and dynamic (production rate and pressure) data. Incorporating dynamic data into the reservoir model is generally known as history matching. History matching is difficult because it poses a nonlinear inverse problem in the sense that the relationship between the reservoir model parameters and the dynamic data is highly nonlinear and multiple solutions are avail- able. Therefore, history matching is often done with a trial-and-error method. In real-world applications of history matching, reservoir engineers manually modify an initial model provided by geoscientists until the production data are matched. The initial model is built based on geological and seismic data. While attempts are usually made to honor these other data as much as possible, often the history-matched models are unrealistic from a geological (and geophysical) point of view. For example, permeability is often altered to increase or decrease flow in areas where a mismatch is observed; however, the permeability alterations usually come in the form of box-shaped or pipe-shaped geometries centered around wells or between wells and tend to be devoid of any geologica. considerations. The primary focus lies in obtaining a history match.


2012 ◽  
Author(s):  
Daniel Arnold ◽  
Oscar Vazquez ◽  
Vasily Demyanov ◽  
Michael A. Christie

2020 ◽  
Vol 10 (3) ◽  
pp. 54-85
Author(s):  
Hamzah Amer Abdulameer ◽  
Dr. Sameera Hamd-Allah

Nasryia oil field is located about 38 Km to the north-west of Nasryia city. The field was discovered in 1975 after doing seismic by Iraqi national oil company. Mishrif formation is a carbonate rock (Limestone and Dolomite) and its thickness reach to 170m. The main reservoir is the lower Mishrif (MB) layer which has medium permeability (3.5-100) md and good porosity (10-25) %. Form well logging interpretation, it has been confirmed the rock type of Mishrif formation as carbonate rock. A ten meter shale layer is separating the MA from MB layer. Environmental corrections had been applied on well logs to use the corrected one in the analysis. The combination of Neutron-Density porosity has been chosen for interpretation as it is close to core porosity. Archie equation had been used to calculate water saturation using corrected porosity from shale effect and Archie parameters which are determined using Picket plot. Using core analysis with log data lead to establish equations to estimate permeability and porosity for non-cored wells. Water saturation form Archie was used to determine the oil-water contact which is very important in oil in place calculation. PVT software was used to choose the best fit PVT correlation that describes reservoir PVT properties which will be used in reservoir and well modeling. Numerical software was used to generate reservoir model using all geological and petrophysical properties. Using production data to do history matching and determine the aquifer affect as weak water drive. Reservoir model calculate 6.9 MMMSTB of oil as initial oil in place, this value is very close to that measured by Chevron study on same reservoir which was 7.1 MMMSTB. [1] Field production strategy had been applied to predict the reservoir behavior and production rate for 34 years. The development strategy used water injection to support reservoir pressure and to improve oil recovery. The result shows that the reservoir has the ability to produce oil at apparently stable rate equal to 85 Kbbl/d, also the recovery factor is about 14%.


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