Estimating recoverable oil reserves using integral displacement characteristics based on probabilistic methodology

2021 ◽  
pp. 78-88
Author(s):  
V. S. Shumko ◽  
E. I. Mamchistova ◽  
S. S. Kuzovlev
Keyword(s):  
Comparative Analysis ◽  
Probabilistic Method ◽  
Hydrodynamic Modeling ◽  
Computational Time ◽  
Actual Problem ◽  
Field Development ◽  
Oil Reserves ◽  
Oil Displacement ◽  
Filtration Properties ◽  
Require Information

Estimation of recoverable oil reserves is an actual problem in field development. One way to estimate reserves is to use the characteristics of oil displacement by water. This method, in contrast to hydrodynamic modeling, doesn't take a long computational time and doesn't require information on the geological and filtration properties of the objects under consideration.The article discusses the use of integral displacement characteristics based on a probabilistic method for assessing potentially recoverable oil reserves. We describe an algorithm for estimating reserves by this method. In the course of the comparative analysis, the efficiency of the method was demonstrated depending on the watercut at the end of the approximation interval. As a result, with a watercut of less than 90 %, a better forecast was found than in the classical application of the characteristics of oil displacement by water.

scholarly journals Technology for Improving the Efficiency of Fractured Reservoir Development Using Gel-Forming Compositions

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8254
Author(s):  
Dmitry Mardashov ◽  
Victor Duryagin ◽  
Shamil Islamov
Keyword(s):  
Fractured Reservoirs ◽  
The Arctic ◽  
High Tech ◽  
Exploratory Research ◽  
Fractured Reservoir ◽  
Field Development ◽  
Oil Reserves ◽  
Chemical Reagents ◽  
Reservoir Development ◽  
Filtration Properties

Increasing the field development efficiency of fractured reservoirs is a contemporary issue. This paper presents fundamental and exploratory research results in this field using modern high-tech experimental equipment from the “Arctic” Scientific Centre at the Saint Petersburg Mining University. Oil reserves in fractured reservoirs are enormous; however, they are classified as hard-to-recover. The before-mentioned reservoirs require a specific approach when selecting technologies to improve the efficiency of their development. In this paper, as a solution to the problem under discussion, we propose the use of a physicochemical method of developing fractured reservoirs based on the injection of a water shut-off agent to exclude highly permeable water-conducting fractures from the drainage process. This technology makes it possible to effectively include and develop previously undrained reservoir areas by directly controlling their filtration properties with the use of new highly efficient and ecologically safe chemical reagents and process fluids.

Oil Reserves Evaluation and Field Development plan of Hakim Oil Field in Libya

2016 ◽  
Vol 18 (1) ◽  
pp. 39-53
Author(s):  
Omar Salih ◽  
Mahmoud Tantawy ◽  
Sayed Elayouty ◽  
Atef Abd Hady
Keyword(s):  
Oil Field ◽  
Development Plan ◽  
Field Development ◽  
Oil Reserves

scholarly journals Scenario reduction methodologies under uncertainties for reservoir development purposes: distance-based clustering and metaheuristic algorithm

2021 ◽  
Author(s):  
Seyed Kourosh Mahjour ◽  
Antonio Alberto Souza Santos ◽  
Manuel Gomes Correia ◽  
Denis José Schiozer
Keyword(s):  
Flow Simulation ◽  
Reduction Process ◽  
Computational Time ◽  
Metaheuristic Algorithm ◽  
Dynamic Data ◽  
Scenario Reduction ◽  
Field Development ◽  
Data Usage ◽  
Simulation Process ◽  
Uncertainty Space

AbstractThe simulation process under uncertainty needs numerous reservoir models that can be very time-consuming. Hence, selecting representative models (RMs) that show the uncertainty space of the full ensemble is required. In this work, we compare two scenario reduction techniques: (1) Distance-based Clustering with Simple Matching Coefficient (DCSMC) applied before the simulation process using reservoir static data, and (2) metaheuristic algorithm (RMFinder technique) applied after the simulation process using reservoir dynamic data. We use these two methods as samples to investigate the effect of static and dynamic data usage on the accuracy and rate of the scenario reduction process focusing field development purposes. In this work, a synthetic benchmark case named UNISIM-II-D considering the flow unit modelling is used. The results showed both scenario reduction methods are reliable in selecting the RMs from a specific production strategy. However, the obtained RMs from a defined strategy using the DCSMC method can be applied to other strategies preserving the representativeness of the models, while the role of the strategy types to select the RMs using the metaheuristic method is substantial so that each strategy has its own set of RMs. Due to the field development workflow in which the metaheuristic algorithm is used, the number of required flow simulation models and the computational time are greater than the workflow in which the DCSMC method is applied. Hence, it can be concluded that static reservoir data usage on the scenario reduction process can be more reliable during the field development phase.

Development of efficiency increase methods for water injection

2020 ◽  
pp. 57-60
Author(s):  
K.I. Mustafaev ◽  
◽  
◽  
Keyword(s):  
Water Injection ◽  
Cost Effective ◽  
Current Interest ◽  
Residual Oil ◽  
Production Well ◽  
Field Development ◽  
Oil Reserves ◽  
Production Wells ◽  
Efficiency Increase

The production of residual oil reserves in the fields being in a long-term exploitation is of current interest. The extraction of residual oil in such fields was cost-effective and simple technological process and is always hot topic for researchers. Oil wells become flooded in the course of time. The appearance of water shows in production wells in the field development and operation is basically negative occurrence and requires severe control. Namely for this reason, the studies were oriented, foremost, to the prevention of water shows in production well and the elimination of its complications as well. The paper discusses the ways of reflux efficiency increase during long-term exploitation and at the final stages of development to prevent the irrigation and water use in production wells.

Iterative modeling is as a tool for selecting a geological basis for hydrodynamic modeling and development design

2021 ◽  
pp. 111-126
Author(s):  
A. A. Agarkova ◽  
S. E. Shebankin ◽  
M. A. Tukaev ◽  
M. S. Karmazin
Keyword(s):  
Initial Data ◽  
Hydrodynamic Modeling ◽  
Usual Method ◽  
Gas Condensate ◽  
Digital Model ◽  
Geological Model ◽  
Field Case ◽  
Field Development ◽  
Wide Range

The usual method for constructing a digital model of a field is based on hydrodynamic modeling using the basic implementation of a geological model, usually requires additional adjustments to the initial data, and as a result, leads to a wide range of uncertainties in assessing the predicted technological indicators of field development. The PK1 reservoir of a gas condensate field case study discuss-es the method of iterative modeling, which makes it possible to comprehensively approach the assessment of possible uncertainties.

DEVELOPMENT PLANNING FOR THE COSSACK AND WANAEA FIELDS

1994 ◽  
Vol 34 (1) ◽  
pp. 92
Author(s):  
G. B. Salter ◽  
W. P. Kerckhoff
Keyword(s):  
Cost Reduction ◽  
Water Injection ◽  
Development Planning ◽  
Oil Field ◽  
Oil Fields ◽  
Oil Reservoirs ◽  
Field Development ◽  
Oil Reserves ◽  
Oil Field Development ◽  
Significant Effort

Development of the Cossack and Wanaea oil fields is in progress with first oil scheduled for late 1995. Wanaea oil reserves are estimated in the order of 32 x 106m3 (200 MMstb) making this the largest oil field development currently underway in Australia.Development planning for these fields posed a unique set of challenges.Key subsurface uncertainties are the requirement for water injection (Wanaea only) and well numbers. Strategies for managing these uncertainties were studied and appropriate flexibility built-in to planned facilities.Alternative facility concepts including steel/concrete platforms and floating options were studied-the concept selected comprises subsea wells tied-back to production/storage/export facilities on an FPSO located over Wanaea.In view of the high proportion of costs associated with the subsea components, significant effort was focussed on flowline optimisation, simplification and cost reduction. These actions have led to potential major economic benefits.Gas utilisation options included reinjection into the oil reservoirs, export for re-injection into North Rankin or export to shore. The latter requires the installation of an LPG plant onshore and was selected as the simplest, safest and the most economically attractive method.

scholarly journals Limitation of gas inflows under the conditions of development of Botuobinsky horizon

2020 ◽  
pp. 159-166
Author(s):  
I. I. Krasnov ◽  
V. F. Tomskaya ◽  
E. I. Inyakina ◽  
K. O. Tomsky ◽  
M. S. Ivanova ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Geological Structure ◽  
Operating Conditions ◽  
Computational Method ◽  
Field Development ◽  
Oil Reserves ◽  
Main Factors ◽  
The Republic ◽  
Effective Development ◽  
Oil Rim

The article presents the results of the study of the geological structure of oil and gas deposits in Botuobinsky horizon, affecting the gasification of producing wells and gas breakthrough into the oil rim in the conditions of field development. In the course of the research, a characteristic of the reservoir was given, and the optimal gas-free flow rate was determined by a computational method, which allows us to limit the gas inflow for the operating conditions of the Srednebotuobinskoye oil and gas condensate field. The field under consideration is one of the unique storehouses of the East-Siberian oil cluster located in the Republic of Sakha (Yakutia). The main factors influencing the effective development of oil reserves of gas and oil deposits within the Central block and the Kurung license area are substantiated.

scholarly journals Efficient Algorithms for E-Healthcare to Solve Multiobject Fuse Detection Problem

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Ijaz Ahmad ◽  
Inam Ullah ◽  
Wali Ullah Khan ◽  
Ateeq Ur Rehman ◽  
Mohmmed S. Adrees ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Comparative Analysis ◽  
Target Detection ◽  
Nearest Neighbor ◽  
Detection Algorithm ◽  
Vital Role ◽  
Computational Time ◽  
K Nearest Neighbor ◽  
Mri Scan ◽  
Video File

Object detection plays a vital role in the fields of computer vision, machine learning, and artificial intelligence applications (such as FUSE-AI (E-healthcare MRI scan), face detection, people counting, and vehicle detection) to identify good and defective food products. In the field of artificial intelligence, target detection has been at its peak, but when it comes to detecting multiple targets in a single image or video file, there are indeed challenges. This article focuses on the improved K-nearest neighbor (MK-NN) algorithm for electronic medical care to realize intelligent medical services and applications. We introduced modifications to improve the efficiency of MK-NN, and a comparative analysis was performed to determine the best fuse target detection algorithm based on robustness, accuracy, and computational time. The comparative analysis is performed using four algorithms, namely, MK-NN, traditional K-NN, convolutional neural network, and backpropagation. Experimental results show that the improved K-NN algorithm is the best model in terms of robustness, accuracy, and computational time.

scholarly journals Performance Analysis of Predictive Models using Generic Datasets

2020 ◽  
Vol 9 (3) ◽  
pp. 3612-3617
Keyword(s):  
Neural Networks ◽  
Comparative Analysis ◽  
Performance Analysis ◽  
Decision Tree ◽  
Predictive Models ◽  
Misclassification Rate ◽  
Computational Time ◽  
Data Sets ◽  
Tree Algorithms

Today over 2.5 quintillion bytes of data is being created every single day where 753 crore people on this planet are creating 1.7mb of data each second. Most often than not, Researchers only scratch the surface when it comes to analyzing which algorithm will be best suited with their dataset and which one will give the highest efficiency. Sometimes, this analysis takes more computational time than the actual execution itself. Aim of this paper is to understand and solve this dilemma by applying different predictions models like Neural Networks, Regression and Decision Tree algorithms to different datasets where their performance was measured using ROC Index, Average Square Error and Misclassification Rate. A comparative analysis is done to show their best performance in different scopes and conditions. All data sets and results were compared and analyzed using SAS tool.

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