Monitoring and Improving Water Injection Efficiency in a Structurally Complex Field

2011 ◽  
Author(s):  
Marco Rotondi ◽  
Andrea Binda ◽  
Mohamed Draoui ◽  
Achille Tsoumou ◽  
Loris Tealdi
Keyword(s):  
Water Injection ◽  
Complex Field ◽  
Injection Efficiency

scholarly journals A New Methodology for the Multilayer Tight Oil Reservoir Water Injection Efficiency Evaluation and Real-Time Optimization

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Lin Cao ◽  
Jianlong Xiu ◽  
Hongjie Cheng ◽  
Hui Wang ◽  
Shujian Xie ◽  
...  
Keyword(s):  
Water Injection ◽  
Sedimentary Facies ◽  
Production Performance ◽  
Water Flooding ◽  
Tight Oil ◽  
Oil Reservoir ◽  
Reservoir Water ◽  
Injection Efficiency ◽  
Tight Oil Reservoir ◽  
Channel Bar

It is important to determine the reasonable injection and production rates in the development of multilayer tight oil reservoir with water flooding treatment. Based on the INSIM (interconnection-based numeric simulation model), a connected network model, a new method is designed to evaluate the water injection efficiency of different layers in water flooding reservoirs and to optimize the injection-production system to produce more oil. Based on the types of sedimentary facies and corresponding injection-production data, the interwell connections are divided into four major categories (middle channel, channel edge, middle channel bar, and channel bar edge) and twelve subclasses. This classification standard of interwell connections could help to significantly improve the accuracy of judging the dominant flow path without constructing a complicated geological model. The interaction of interwells such as injection-production correlation and water injection efficiency could be revealed by simulating the production performance and computing the layer dividing coefficient and well dividing coefficient. A numerical example is used to validate this method by comparing results from FrontSim and this method, and the computational efficiency of this method is several dozen times faster than that of the traditional numerical simulation. This method is applied to quickly optimize the production schedule of a tight oil reservoir with the water flooding treatment, that is, the water injection rate of multilayer reservoirs could be optimized subtly by the injection efficiency of different layers, and the target of producing more oil with lower water cut could be achieved.

A Practical Model for Water Injection Evaluation and Optimization in Typical Offshore Reservoirs Considering Formation Heterogeneity Based on Experimental Study

2021 ◽  
Author(s):  
Shijun Huang ◽  
Yuanrui Zhu ◽  
Shichao Chai ◽  
Guanyang Ding ◽  
Yicheng Xin ◽  
...  
Keyword(s):  
Horizontal Well ◽  
Superposition Principle ◽  
Water Injection ◽  
Injection Rate ◽  
Rate Curve ◽  
Control Effect ◽  
Injection Efficiency ◽  
Profile Control ◽  
Horizontal Wellbore ◽  
Heterogeneous Formation

Abstract A major concern with water injection in offshore oil reservoir is the water breakthrough. The formation heterogeneity is the main reason for it. In order to evaluate the water injection efficiency, a visualized 2-D experiment was carried out to obtain the distribution law of injected water and the variation of injection parameters in homogeneous and heterogeneous formation. In addition, a coupled wellbore/reservoir model was established by applying microelement method, superposition principle and imaging. This model considers the formation heterogeneity and pressure drop caused by wellbore friction. The visualized 2-D sand filling displacement experiment indicates that the injection rate at the horizontal well heel is greater than that at the toe and the injection front is more irregular in heterogeneous formation. The injection rate and injection pressure distribution along the horizontal well are obtained analytically based on the proposed model, the results show that the injection rate at the two sides of the wellbore is much higher than that in the middle when the formation is homogeneous and the wellbore is infinite-conductive. In this case, the injection rate curve along horizontal well shows a "U" shaped distribution. When a finite-conductive horizontal wellbore is considered, the injection rate at the heel of the wellbore is higher than that of the toe, although the injection rate curve along horizontal well also exhibits a deformed "U" shape distribution. For the formation heterogeneities along the horizontal wellbore, the injection rate distribution curve is not continuous anymore, but a deformed "U" shape is also observed for each wellbore segment. At last, the established model was applied to an ultra-heterogeneous offshore reservoir. It is concluded that the profile control effect of typical well is obvious. The results of this study are of great significance for the calculation of the injection rate profile and improving the water injection efficiency.

scholarly journals An injection optimization decision-making tool using streamline based fuzzy logic workflow

2021 ◽  
Author(s):  
Nader Y. BuKhamseen ◽  
Abdullah A. Al-Najem ◽  
Ali H. Saffar
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Water Injection ◽  
Fuzzy Logic System ◽  
Injection Efficiency ◽  
Area Of Interest ◽  
Well Pattern ◽  
Reservoir Simulator ◽  
Decision Making Tool ◽  
Logic System

AbstractThis paper presents an adaptive approach to optimize field injection strategies using streamline-based well allocations coupled with fuzzy logic. The strength of our approach comes from the fact that streamlines are generated by running a full-physics reservoir simulator. Streamlines provide great insights about well pattern connectivity and good allocation factors allowing the injection efficiency (IE) for each pattern to be determined. Fuzzy logic can simulate human thinking and handle different categories of information including linguistic, imprecise, approximate, and overlapping to name a few. This paper presents a genuine approach for field injection optimization using a streamlined-based fuzzy logic system. In this work, we present an adaptive streamline-based fuzzy logic system that uses three input parameters namely injection efficiency (IE), water cut (WC), and injection loss to aquifer to assign an injector ranking index (IRI) according to injector performances. The workflow then smartly redistributes water injection by accounting for operational constraints and number of connected producers in a pattern in addition to the IRI. The workflow examines the low performers (i.e., low and medium IRI categories) and assigns different injection reduction factors for each injector in these categories. Then, the total amount of reduced injection is assigned to high performers (i.e., high IRI) while ensuring no operational constraint is violated, such as bottom-hole pressure (BHP) and capacity of pumps. This approach has been tested on a dual-porosity dual-permeability (DPDP) conceptual simulation model. The area of interest has two rows of injectors: downdip and updip. The updip injectors are the focus of the study. The results of applying this approach show noticeable improvements in injection efficiency for most wells in the area of interest ensuring better sweep, good pressure support, and improving cumulative oil production. We believe combining both technologies, namely streamlines and fuzzy logic, can provide reservoir engineers with a robust decision-making tool to attain a more successful field-wide water injection strategy.

scholarly journals A Novel Data-Driven Model for Dynamic Prediction and Optimization of Profile Control in Multilayer Reservoirs

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wei Liu ◽  
Hui Zhao ◽  
Xun Zhong ◽  
Guanglong Sheng ◽  
Meilong Fu ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Parameter Optimization ◽  
Water Injection ◽  
Material Balance ◽  
Data Driven ◽  
Production Data ◽  
Daily Production ◽  
Injection Efficiency ◽  
Profile Control ◽  
Actual Field

Establishing reservoir numerical simulation and profile control optimization methods considering the mechanism of profile control has always been a difficult research problem at home and abroad. In this paper, firstly, a physics-based data-driven model was established on daily production data of injection and production wells following the principle of material balance. Key parameters including transmissibility, control pore volume, water injection allocation factors, and injection efficiency are derived directly from history matched model, and the dominated flow channels could be quantitatively identified. Then, combined with the evaluation results of the plugging ability of the plugging agent, imaginary well nodes are added to the existing interwell relationship to characterize the heterogeneity of interwell-specific parameters. This process performs flow processing along the interwell control units, forming a new and rapid method for simulation and prediction. Lastly, based on the calculated interwell transmissibility, water injection efficiency, and allocation factors, injection wells with low water injection efficiency can be preferentially selected as profile control wells. In addition, taking the production rates, injection rates, and the amount of plugging agent as optimization variables, we established an optimal control mathematical model and realized the parameter optimization method of the profile control. We demonstrated the results of one conceptual model and two indoor experiments to verify the feasibility of the proposed method and completed two actual field applications. Model validation and actual field application show that the proposed method successfully eliminates the complicated geological modeling procedure and the tedious calculation process associated with the profile control treatment in traditional numerical simulation methods. The calculation speed improves tens or hundreds of times, and water channeling paths are accurately identified. Most importantly, this method realizes the overall decision-making of profile control well selection, dynamic production prediction, and parameter optimization of profile control measures quickly and accurately by mainly using the daily production data of wells. The findings of this study can help for better understanding of the optimization design and application of on-site profile control schemes in large-scale oilfields.

Identifying Patterns in Complex Field Data

2017 ◽  
Vol 225 (3) ◽  
pp. 268-284 ◽  
Author(s):  
Andrew J. White ◽  
Dieter Kleinböhl ◽  
Thomas Lang ◽  
Alfons O. Hamm ◽  
Alexander L. Gerlach ◽  
...  
Keyword(s):  
Heart Rate ◽  
Panic Disorder ◽  
Latent Class ◽  
Treatment Protocol ◽  
Situational Factors ◽  
Self Report ◽  
Complex Field ◽  
Cluster Assignment ◽  
Experimental Conditions ◽  
Conventional Analysis

Abstract. Ambulatory assessment methods are well suited to examine how patients with panic disorder and agoraphobia (PD/A) undertake situational exposure. But under complex field conditions of a complex treatment protocol, the variability of data can be so high that conventional analytic approaches based on group averages inadequately describe individual variability. To understand how fear responses change throughout exposure, we aimed to demonstrate the incremental value of sorting HR responses (an index of fear) prior to applying averaging procedures. As part of their panic treatment, 85 patients with PD/A completed a total of 233 bus exposure exercises. Heart rate (HR), global positioning system (GPS) location, and self-report data were collected. Patients were randomized to one of two active treatment conditions (standard exposure or fear-augmented exposure) and completed multiple exposures in four consecutive exposure sessions. We used latent class cluster analysis (CA) to cluster heart rate (HR) responses collected at the start of bus exposure exercises (5 min long, centered on bus boarding). Intra-individual patterns of assignment across exposure repetitions were examined to explore the relative influence of individual and situational factors on HR responses. The association between response types and panic disorder symptoms was determined by examining how clusters were related to self-reported anxiety, concordance between HR and self-report measures, and bodily symptom tolerance. These analyses were contrasted with a conventional analysis based on averages across experimental conditions. HR responses were sorted according to form and level criteria and yielded nine clusters, seven of which were interpretable. Cluster assignment was not stable across sessions or treatment condition. Clusters characterized by a low absolute HR level that slowly decayed corresponded with low self-reported anxiety and greater self-rated tolerance of bodily symptoms. Inconsistent individual factors influenced HR responses less than situational factors. Applying clustering can help to extend the conventional analysis of highly variable data collected in the field. We discuss the merits of this approach and reasons for the non-stereotypical pattern of cluster assignment across exposures.

STUDY ON SUBCOOLED WATER INJECTION INTO MOLTEN MATERIAL

1998 ◽  
Author(s):  
Hyun Sun Park ◽  
Norihiro Yamano ◽  
Kiyofumi Moriyama ◽  
Yu Maruyama ◽  
Yanhua Yang ◽  
...  
Keyword(s):  
Water Injection ◽  
Molten Material ◽  
Subcooled Water
Sign in / Sign up

Export Citation Format

Share Document