Practical Considerations when Using Capacitance Resistance Modelling CRM for Waterflood Optimization

2021 ◽  
Author(s):  
Srungeer Simha ◽  
Manu Ujjwal ◽  
Gaurav Modi
Keyword(s):  
Optimization Technique ◽  
Material Balance ◽  
Fractional Flow ◽  
Blind Test ◽  
History Match ◽  
Flow Solver ◽  
Analytical Technique ◽  
Primary Driver ◽  
Simplifying Assumptions ◽  
Using Data

Abstract Capacitance resistance modeling (CRM) is a data-driven analytical technique for waterflood optimization developed in the early 2000s. The popular implementation uses only production/injection data as input and makes simplifying assumptions of pressure maintenance and injection being the primary driver of production. While these assumptions make CRM a quick plug & play type of technique that can easily be replicated between assets they also lead to major pitfalls, as these assumptions are often invalid. This study explores these pitfalls and discusses workarounds and mitigations to improve the reliability of CRM. CRM was used as a waterflood optimization technique for 3 onshore oil fields, each having 100s of active wells, multiple stacked reservoirs, and over 15 years of pattern waterflood development. The CRM algorithm was implemented in Python and consists of 4 modules: 1) Connectivity solver module – where connectivity between injectors and producers is quantified using a 2 year history match period, 2) Fractional Flow solver module – where oil rates are established as a function of injection rates, 3) Verification module – which is a blind test to assess history match quality, 4) Waterflood optimizer module – which redistributes water between injectors, subject to facility constraints and estimates potential oil gain. Additionally, CRM results were interpreted and validated using an integrated visualization dashboard. The two main issues encountered while using CRM in this study are 1) poor history match (HM) and 2) very high run time in the order of tens of hours due to the large number of wells. Poor HM was attributed to significant noise in the production data, aquifer support contributing to production, well interventions such as water shut-offs, re-perforation, etc. contributing to oil production. These issues were mitigated, and HM was improved using data cleaning techniques such as smoothening, outlier removal, and the usage of pseudo aquifer injectors for material balance. However, these techniques are not foolproof due to the nature of CRM which relies only on trends between producers and injectors for waterflood optimization. Runtime however was reduced to a couple of hours by breaking up the reservoir into sectors and using parallelization.

scholarly journals Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique

2021 ◽  
Vol 13 (12) ◽  
pp. 6644
Author(s):  
Ali Selim ◽  
Salah Kamel ◽  
Amal A. Mohamed ◽  
Ehab E. Elattar
Keyword(s):  
Power System ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Optimization Technique ◽  
Mathematical Formulation ◽  
Optimization Techniques ◽  
Sensitivity Factor ◽  
Hybrid Technique ◽  
Analytical Technique

In recent years, the integration of distributed generators (DGs) in radial distribution systems (RDS) has received considerable attention in power system research. The major purpose of DG integration is to decrease the power losses and improve the voltage profiles that directly lead to improving the overall efficiency of the power system. Therefore, this paper proposes a hybrid optimization technique based on analytical and metaheuristic algorithms for optimal DG allocation in RDS. In the proposed technique, the loss sensitivity factor (LSF) is utilized to reduce the search space of the DG locations, while the analytical technique is used to calculate initial DG sizes based on a mathematical formulation. Then, a metaheuristic sine cosine algorithm (SCA) is applied to identify the optimal DG allocation based on the LSF and analytical techniques instead of using random initialization. To prove the superiority and high performance of the proposed hybrid technique, two standard RDSs, IEEE 33-bus and 69-bus, are considered. Additionally, a comparison between the proposed techniques, standard SCA, and other existing optimization techniques is carried out. The main findings confirmed the enhancement in the convergence of the proposed technique compared with the standard SCA and the ability to allocate multiple DGs in RDS.

Short Term Injection Re-Distribution STIR: Real-Time Waterflood Optimization Technique Using Advanced Data Analytics

2021 ◽  
Author(s):  
Gaurav Modi ◽  
Manu Ujjwal ◽  
Srungeer Simha
Keyword(s):  
Real Time ◽  
Data Analytics ◽  
Optimization Technique ◽  
Material Balance ◽  
Oil Production ◽  
Data Driven ◽  
Petroleum Engineering ◽  
Short Term ◽  
Injection Water ◽  
Facility Level

Abstract Short Term Injection Re-distribution (STIR) is a python based real-time WaterFlood optimization technique for brownfield assets that uses advanced data analytics. The objective of this technique is to generate recommendations for injection water re-distribution to maximize oil production at the facility level. Even though this is a data driven technique, it is tightly bounded by Petroleum Engineering principles such as material balance etc. The workflow integrates and analyse short term data (last 3-6 months) at reservoir, wells and facility level. STIR workflow is divided into three modules: Injector-producer connectivity Injector efficiency Injection water optimization First module uses four major data types to estimate the connectivity between each injector-producer pair in the reservoir: Producers data (pressure, WC, GOR, salinity) Faults presence Subsurface distance Perforation similarity – layers and kh Second module uses connectivity and watercut data to establish the injector efficiency. Higher efficiency injectors contribute most to production while poor efficiency injectors contribute to water recycling. Third module has a mathematical optimizer to maximize the oil production by re-distributing the injection water amongst injectors while honoring the constraints at each node (well, facility etc.) of the production system. The STIR workflow has been applied to 6 reservoirs across different assets and an annual increase of 3-7% in oil production is predicted. Each recommendation is verified using an independent source of data and hence, the generated recommendations align very well with the reservoir understanding. The benefits of this technique can be seen in 3-6 months of implementation in terms of increased oil production and better support (pressure increase) to low watercut producers. The inherent flexibility in the workflow allows for easy replication in any Waterflooded Reservoir and works best when the injector well count in the reservoir is relatively high. Geological features are well represented in the workflow which is one of the unique functionalities of this technique. This method also generates producers bean-up and injector stimulation candidates opportunities. This low cost (no CAPEX) technique offers the advantages of conventional petroleum engineering techniques and Data driven approach. This technique provides a great alternative for WaterFlood management in brownfield where performing a reliable conventional analysis is challenging or at times impossible. STIR can be implemented in a reservoir from scratch in 3-6 weeks timeframe.

scholarly journals Accurate and efficient representation of intramolecular energy inab initiogeneration of crystal structures. I. Adaptive local approximate models

2016 ◽  
Vol 72 (6) ◽  
pp. 864-874 ◽  
Author(s):  
Isaac Sugden ◽  
Claire S. Adjiman ◽  
Constantinos C. Pantelides
Keyword(s):  
Structure Prediction ◽  
Computational Cost ◽  
Search Space ◽  
Approximate Model ◽  
High Energy ◽  
Computational Effort ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Acta Cryst ◽  
Simplifying Assumptions

The global search stage of crystal structure prediction (CSP) methods requires a fine balance between accuracy and computational cost, particularly for the study of large flexible molecules. A major improvement in the accuracy and cost of the intramolecular energy function used in theCrystalPredictor II[Habgoodet al.(2015).J. Chem. Theory Comput.11, 1957–1969] program is presented, where the most efficient use of computational effort is ensuredviathe use of adaptive local approximate model (LAM) placement. The entire search space of the relevant molecule's conformations is initially evaluated using a coarse, low accuracy grid. Additional LAM points are then placed at appropriate points determinedviaan automated process, aiming to minimize the computational effort expended in high-energy regions whilst maximizing the accuracy in low-energy regions. As the size, complexity and flexibility of molecules increase, the reduction in computational cost becomes marked. This improvement is illustrated with energy calculations for benzoic acid and the ROY molecule, and a CSP study of molecule (XXVI) from the sixth blind test [Reillyet al.(2016).Acta Cryst.B72, 439–459], which is challenging due to its size and flexibility. Its known experimental form is successfully predicted as the global minimum. The computational cost of the study is tractable without the need to make unphysical simplifying assumptions.

Fixed-Antenna Pointing-Angle Calibration of Airborne Doppler Cloud Radar

2013 ◽  
Vol 30 (10) ◽  
pp. 2320-2335 ◽  
Author(s):  
Samuel Haimov ◽  
Alfred Rodi
Keyword(s):  
Optimization Technique ◽  
Measurement Unit ◽  
Doppler Velocity ◽  
Velocity Measurements ◽  
Antenna Beam ◽  
Cloud Radar ◽  
Aircraft Motion ◽  
Antenna Phase Center ◽  
Using Data ◽  
Wind Retrievals

Abstract Doppler velocity measurements from airborne meteorological Doppler radars require removal of the aircraft motion contribution in order to provide radial velocity of hydrometeor targets. This is a critical step for hydrometeor motion and wind retrievals. The aircraft motion contribution is defined as the scalar product between the radar antenna beam-pointing vector and the aircraft velocity vector at the antenna phase center. The accuracy in the removal of the aircraft velocity contribution is determined by the accuracy of the beam-pointing vector, the rigidity of the antenna mount, and the accuracy of the aircraft attitude and velocity measurements. In this paper an optimization technique is proposed to determine the antenna beam-pointing vector and to analyze its uncertainties using aircraft attitude and velocity data from a GPS-aided inertial measurement unit and radar observations of the earth surface. The technique is applied to Wyoming Cloud Radar (WCR) on the University of Wyoming King Air (UWKA) aircraft. The beam-pointing vectors of the two fixed downward-pointing WCR antennas are calibrated using data selected from several calibration flights. The maximum root-mean-square error in the calibrated beam-pointing angles is smaller than 0.03°, resulting in less than 0.1 m s−1 aircraft motion residual error in the Doppler velocities after removing the aircraft motion contribution. Some applicability and limitations to other airborne Doppler radars with fixed antennas are discussed.

scholarly journals Analysis of ionospheric electrodynamic parameters on mesoscales – a review of selected techniques using data from ground-based observation networks and satellites

2011 ◽  
Vol 29 (3) ◽  
pp. 467-491 ◽  
Author(s):  
H. Vanhamäki ◽  
O. Amm
Keyword(s):  
Data Analysis ◽  
Data Sets ◽  
Practical Applications ◽  
Analysis Methods ◽  
Ionospheric Electrodynamics ◽  
Simplifying Assumptions ◽  
Using Data ◽  
Measured Input ◽  
Data Analysis Methods ◽  
Selection Of

Abstract. We present a review of selected data-analysis methods that are frequently applied in studies of ionospheric electrodynamics and magnetosphere-ionosphere coupling using ground-based and space-based data sets. Our focus is on methods that are data driven (not simulations or statistical models) and can be used in mesoscale studies, where the analysis area is typically some hundreds or thousands of km across. The selection of reviewed methods is such that most combinations of measured input data (electric field, conductances, magnetic field and currents) that occur in practical applications are covered. The techniques are used to solve the unmeasured parameters from Ohm's law and Maxwell's equations, possibly with help of some simplifying assumptions. In addition to reviewing existing data-analysis methods, we also briefly discuss possible extensions that may be used for upcoming data sets.

scholarly journals A Novel Analytical Curve for Forecasting and Monitoring Gasflood Performance

2015 ◽  
Vol 8 (1) ◽  
pp. 29-37
Author(s):  
Kaijun Tong ◽  
Lizhen Ge ◽  
Fei Shi ◽  
Zhiqiang Zhu ◽  
Lingling Nie
Keyword(s):  
Performance Monitoring ◽  
Material Balance ◽  
Monitoring And Evaluation ◽  
Production Performance ◽  
Fractional Flow ◽  
Segregated Flow ◽  
Analytical Curve ◽  
Function Relationship ◽  
Gas Drive ◽  
And Control

With the increasing proportion of gas cap & artificial gas injection reservoirs, production performance monitoring and evaluation of gas-drive reservoir are becoming more and more important. However, there is no efficient method to forecast the production performance of gas-drive reservoir. In this paper, the analysis starts from the statistics of oil/gas relative permeability data of cores experiments. Based on fundamental principles of segregated flow and material balance, a new analytical curve of gasflood was developed to analyze the production performance. We applied the novel analytical curve to the production data from 23 gas-drive reservoirs at home and abroad and found a better power function relationship between dynamic reserves (N) and the slope (B) as foreseen by the analytical curve. It has been shown that the slope of the new curve represents dynamic reserves value; the smaller the slope value is, the more dynamic reserves are. Furthermore, by introducing the economic limit gas-oil ratio and control conditions which include initial and boundary conditions, a chart of dimensionless fractional flow of gas vs. recovery percent of OOIP is established to evaluate oilfield development rapidly and intuitively. Finally, many examples of application confirmed strongly that the new analytical curve used in gas-drive reservoirs is practical and effective, which broadens the scope of gas-drive oilfield research.

Shakedown Analysis of a Finite Plate With Single Edge Notch Under Uniaxial Tension

2000 ◽  
Author(s):  
M. S. Attia ◽  
M. Abdel-Karim ◽  
M. M. Megahed
Keyword(s):  
Optimization Technique ◽  
Analytical Techniques ◽  
Load Factor ◽  
Single Edge ◽  
Analytical Technique ◽  
Single Edge Notch ◽  
Elastic Stresses ◽  
Gradient Optimization ◽  
Edge Notch ◽  
Elastic Compensation Method

Abstract In this paper, the shakedown load factor for a finite rectangular plate with a single edge notch at its mid-length is evaluated by a number of numerical and analytical techniques. These techniques include full elasto-plastic finite element solution coupled with line search technique and an iterative elastic technique known as the elastic compensation method which relies on successive reduction of elastic modulus in regions where elastic stresses exceed yield strength. In addition, an analytical technique proposed recently in the literature, which relies on a gradient optimization technique is employed. The shakedown load factor values obtained through different solution techniques are compared. The comparison showed discrepancies between literature solutions and the solutions presented herein. The reasons behind this discrepancy are scrutinized and certain recommendations are made to ensure validity of shakedown solutions.

Upaya Perlindungan Pesisir dan Pulau-Pulau Kecil Pemerintah Provinsi Sumatera Barat dari Ancaman Abrasi dan Perubahan Iklim

2022 ◽  
Vol 20 (2) ◽  
pp. 302-315
Author(s):  
Amarulla Octavian ◽  
Marsetio Marsetio ◽  
Abimanyu Hilmawan ◽  
Rizqi Rahman
Keyword(s):  
Climate Change ◽  
Local Government ◽  
Coastal Area ◽  
Small Islands ◽  
Data Display ◽  
Analytical Technique ◽  
Living Space ◽  
Depth Interview ◽  
Unique Approach ◽  
Using Data

Kerusakan pesisir dan pulau-pulau kecil akibat abrasi dan dampak perubahan iklim di Provinsi Sumatera Barat sudah di tingkat yang mengkhawatirkan. Kondisi geografis Sumatera Barat yang berhadapan langsung dengan Samudera Hindia membuat sifat tumbukan gelombang di pesisir relatif kuat sehingga abrasi berlangsung dengan cepat. Kerusakan ekosistem mangrove akibat penebangan, alih fungsi lahan, pencemaran muara, dan kerusakan terumbu karang akibat penggunaan bom, potas, dan pemutihan karang, turut mempercepat terjadinya abrasi. Kerusakan pesisir dan pulau-pulau kecil perlu dicegah karena dapat mengurangi keunggulan strategis pertahanan di wilayah terluar, mengganggu efektivitas fungsi infrastruktur sipil dan militer di pesisir, mengganggu stabilitas ekonomi dan mengurangi ruang hidup masyarakat, membahayakan navigasi, dan mengancam keanekaragaman hayati. Tujuan penelitian ini adalah untuk mengetahui sumberdaya dan upaya pemerintah daerah Provinsi Sumatera Barat dalam melindungi pesisir dan pulau-pulau kecil dari abrasi dan dampak perubahan iklim. Penelitian dilaksanakan pada 15-23 September 2019 di Kota Padang dan di Pulau Sipora. Pengumpulan data dilakukan dengan metode observasi, dan wawancara mendalam kepada pejabat instansi pemerintah daerah dan warga di sekitar pesisir. Data dianalisis menggunakan teknik data condensation, data display, dan conclusion drawing. Hasil penelitian menunjukkan instansi-instansi daerah memiliki keunggulan uniknya masing-masing dalam mendukung pencegahan abrasi dan adaptasi perubahan iklim, namun upaya-upaya yang dilaksanakan masih bersifat sporadis, reaktif, tidak terkoordinasi, dan tidak berkelanjutan. Sumber daya bahan baku untuk pencegahan abrasi dan adaptasi perubahan iklim tersedia melimpah di Sumatera Barat, namun sumber daya keorganisasian yang dimiliki instansi daerah relatif terbatas. Kondisi ini membuat abrasi dan dampak perubahan iklim tidak dapat dicegah secara efektif.ABSTRACTWest Sumatera Province has an alarming rate of coastal and small islands destruction caused by abrasion and the effect of climate change. Geographical characteristic of West Sumatera Province which directly face Hindia Ocean quickly have it’s coastal area eroded with abrasion caused by a strong wave. The destruction of mangrove forest and coral reefs further made the abrasion process worse. Coastal and small islands destruction need to be stopped because it could reduce military strategic advantage in national outer areas, reducing the effectiveness of military and civilian infrastructures, destabilizing economy and narrowing the living space of people, endangering the safety of ship navigation, and threatening nature’s biodiversity. The aim of this research is to understand the resources and actions of West Sumatera Province’s local government of how it protect the coastal area and small islands from abrasion and to adapt to the effects of climate change. The research was conducted in September 15 to 23 in 2019 at Padang City and Sipora Island of Kepulauan Mentawai Regency. Data collected by field observation and in-depth interview to officials from local government and the locals. Data analyzed by using data condensation, data display, and conclusion drawing analytical technique. The research shows that each provincional departments under West Sumatera Province local government have it’s own unique approach and technique to prevent abrasion and adapt to the effects of climate change, but the action taken usually implemented sporadically, reactive, uncoordinated, and not sustainable. Natural resources needed to prevent abrasion and to adapt to climate change are abundant, but the Province’s organisational resources is limited, causing the coastal area and small islands innefectively protected 

scholarly journals Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads

2021 ◽  
Vol 13 (8) ◽  
pp. 4447
Author(s):  
Amal A. Mohamed ◽  
Salah Kamel ◽  
Ali Selim ◽  
Tahir Khurshaid ◽  
Sang-Bong Rhee
Keyword(s):  
Optimal Allocation ◽  
Optimization Technique ◽  
Hybrid Approach ◽  
Optimization Techniques ◽  
Constant Current ◽  
Hybrid Technique ◽  
Voltage Profile ◽  
Analytical Technique ◽  
Metaheuristic Optimization ◽  
Different Types

The optimal location of renewable distributed generations (DGs) into a radial distribution system (RDS) has attracted major concerns from power system researchers in the present years. The main target of DG integration is to improve the overall system performance by minimizing power losses and improving the voltage profile. Hence, this paper proposed a hybrid approach between an analytical and metaheuristic optimization technique for the optimal allocation of DG in RDS, considering different types of load. A simple analytical technique was developed in order to determine the sizes of different and multiple DGs, and a new efficient metaheuristic technique known as the Salp Swarm Algorithm (SSA) was suggested in order to choose the best buses in the system, proportionate to the sizes determined by the analytical technique, in order to obtain the minimum losses and the best voltage profile. To verify the power of the proposed hybrid technique on the incorporation of the DGs in RDS, it was applied to different types of static loads; constant power (CP), constant impedance (CZ), and constant current (CI). The performance of the proposed algorithm was validated using two standards RDSs—IEEE 33-bus and IEEE 69-bus systems—and was compared with other optimization techniques.

Sign in / Sign up

Export Citation Format

Share Document