An Integrated IR4.0 Software Enables Autonomous Casing Crossflow Rate Calculation

2021 ◽  
Author(s):  
Nasser M. Al-Hajri ◽  
Akram R. Barghouti ◽  
Sulaiman T. Ureiga
Keyword(s):  
Industrial Revolution ◽  
Water Injection ◽  
Flow Characteristics ◽  
Injection Rate ◽  
Performance Model ◽  
Injection Well ◽  
Production Model ◽  
Well Performance ◽  
Secondary Formation ◽  
Well Model

Abstract This paper will present an alternative calculation technique to predict wellbore crossflow rate in a water injection well resulting from a casing leak. The method provides a self-governing process for wellbore related calculations inspired by the fourth industrial revolution technologies. In an earlier work, calculations techniques were presented which do not require the conventional use of downhole flowmeter (spinner) to obtain the flow rate. Rather, continuous surface injection data prior to crossflow development and shut-in well are used to estimate the rate. In this alternative methodology, surface injection data post crossflow development are factored in to calculate the rate with the same accuracy. To illustrate the process an example water injector well is used. To quantify the casing leak crossflow rate, the following calculation methodology was applied:Generate a well performance model using pre-crossflow injection data. Normal modeling techniques are applied in this step to obtain an accurate model for the injection well as a baseline case.Generate an imaginary injection well model: An injection well mimicking the flow characteristics and properties of the water injector is envisioned to simulate crossflow at flowing (injecting) conditions. In this step, we simulate an injector that has total depth up to the crossflow location only and not the total depth of the example water well.Generate the performance model for the secondary formation using post crossflow data: The total injection rate measured at surface has two portions: one portion goes into the shallower secondary formation and another goes into the deeper (primary) formation. The modeling inputs from the first two steps will be used here to obtain the rate for the downhole formation at crossflow conditions.Generate an imaginary production well model: The normal model for the water injector will be inversed to obtain a production model instead. The inputs from previous steps will be incorporated in the inverse modeling.Obtaining the crossflow rate at shut-in conditions: Performance curves generated from step 3 & 4 will be plotted together to obtain an intersection that corresponds to the crossflow rate at shut-in conditions. This numerical methodology was analytically derived and the prediction results were verified on syntactic field data with very high accuracy. The application of this model will benefit oil operators by avoiding wireline logging costs and associated safety risks with mechanical intervention.

The New Generation of Outflow Control Devices Autonomously Controlling the Conformance of Water Injection Well- A Case Study with ADNOC Onshore

2021 ◽  
Author(s):  
Sultan Ibrahim Al Shemaili ◽  
Ahmed Mohamed Fawzy ◽  
Elamari Assreti ◽  
Mohamed El Maghraby ◽  
Mojtaba Moradi ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Dynamic Properties ◽  
Short Circuit ◽  
Water Injection ◽  
Performance Outcomes ◽  
Injection Well ◽  
Well Performance ◽  
Injection Wells ◽  
Horizontal Section ◽  
Control Devices

Abstract Several techniques have been applied to improve the water conformance of injection wells to eventually improve field oil recovery. Standalone Passive flow control devices or these devices combined with Sliding sleeves have been successful to improve the conformance in the wells, however, they may fail to provide the required performance in the reservoirs with complex/dynamic properties including propagating/dilating fractures or faults and may also require intervention. This is mainly because the continuously increasing contrast in the injectivity of a section with the feature compared to the rest of the well causes diverting a great portion of the injected fluid into the thief zone which ultimately creates short-circuit to the nearby producer wells. The new autonomous injection device overcomes this issue by selectively choking the injection of fluid into the growing fractures crossing the well. Once a predefined upper flowrate limit is reached at the zone, the valves autonomously close. Well A has been injecting water into reservoir B for several years. It has been recognised from the surveys that the well passes through two major faults and the other two features/fractures with huge uncertainty around their properties. The use of the autonomous valve was considered the best solution to control the water conformance in this well. The device initially operates as a normal passive outflow control valve, and if the injected flowrate flowing through the valve exceeds a designed limit, the device will automatically shut off. This provides the advantage of controlling the faults and fractures in case they were highly conductive as compared to other sections of the well and also once these zones are closed, the device enables the fluid to be distributed to other sections of the well, thereby improving the overall injection conformance. A comprehensive study was performed to change the existing dual completion to a single completion and determine the optimum completion design for delivering the targeted rate for the well while taking into account the huge uncertainty around the faults and features properties. The retrofitted completion including 9 joints with Autonomous valves and 5 joints with Bypass ICD valves were installed in the horizontal section of the well in six compartments separated with five swell packers. The completion was installed in mid-2020 and the well has been on the injection since September 2020. The well performance outcomes show that new completion has successfully delivered the target rate. Also, the data from a PLT survey performed in Feb 2021 shows that the valves have successfully minimised the outflow toward the faults and fractures. This allows achieving the optimised well performance autonomously as the impacts of thief zones on the injected fluid conformance is mitigated and a balanced-prescribed injection distribution is maintained. This paper presents the results from one of the early installations of the valves in a water injection well in the Middle East for ADNOC onshore. The paper discusses the applied completion design workflow as well as some field performance and PLT data.

Water Hammer Effects on Water Injection Well Performance and Longevity

2008 ◽  
Author(s):  
Xiuli Wang ◽  
Knut Arne Hovem ◽  
Daniel Moos ◽  
Youli Quan
Keyword(s):  
Water Injection ◽  
Water Hammer ◽  
Injection Well ◽  
Well Performance

Water Injection Well Performance and Fracture Propagation in a Channel Sand Reservoir: An Offshore Ghana Case Study

2019 ◽  
Author(s):  
Jongsoo Hwang ◽  
Prateek Bhardwaj ◽  
Mukul Sharma ◽  
Sekhar Sathyamoorthy ◽  
Kwarteng Amaning ◽  
...  
Keyword(s):  
Water Injection ◽  
Fracture Propagation ◽  
Injection Well ◽  
Well Performance

Real-Time Gas Lift Well Optimization Using Surface Read Out (SRO) System in Bunyu Field

2021 ◽  
Author(s):  
C. F. Amiin
Keyword(s):  
Real Time ◽  
Gas Injection ◽  
Injection Rate ◽  
Performance Model ◽  
Rate Variation ◽  
Production Test ◽  
Total Production ◽  
Well Performance ◽  
Production Forecast ◽  
Gas Lift

Gas lift optimization is required to sustain production in Bunyu Field. There are 35 gas lifted wells from total of 61 production wells, which contribute to2916 BOPD from the total production of 6000 BOPD or around 49% of the total production. The performance of these wells are pivotal to ensure production target is achieved. An optimum gas injection rate in each well is essential to maximize the oil production by reducing the Flowing Bottom Hole Pressure (FBHP). Previously, a conventional downhole Pressure – Temperature (P-T) gauge was used to record well response to gas lift injection rate variation to determine the optimum point. However, this method is considered time consuming since the adjustment to determine the optimum gas injection rate can only be done after the data has been downloaded and being analyzed . Thus, the measurement program should be repeated several times until the optimum gas injection rate is determined. This paper presents an approach to optimize the production of gas lifted well by selecting the optimum gas injection rate using a real-time downhole data monitoring system, called Surface Read Out (SRO). This system is used to evaluate the changes in the downhole pressure and temperature in a real-time. When the downhole P-T gauge reaches the perforation depth, a Multi-Rate Test (MRT) is carried out with variation in gas injection rate to find the optimum rate. Optimum gas injection rate is then determined based on the lowest FBHP observed and the highest production test result during the MRT. This optimization method has been proven effective to quickly increasing well production because gas injection rate adjustment can be done during the measurement program based on the real-time analysis. In addition, calibration of well performance model based on the actual Gas Lift Performance Curve (GLPC) of the MRT result can provide more accurate production forecast.

CALCULATION OF OPTIMAL INJECTION RATE FOR DISPERSED WATERFLOODING SYSTEM

2017 ◽  
pp. 63-67
Author(s):  
L. A. Vaganov ◽  
A. Yu. Sencov ◽  
A. A. Ankudinov ◽  
N. S. Polyakova
Keyword(s):  
Injection Rate ◽  
Oil Field ◽  
Injection Well ◽  
Water Migration ◽  
Mutual Location ◽  
Optimal Injection ◽  
Technical Measures ◽  
Injection Rates

The article presents a description of the settlement method of necessary injection rates calculation, which is depended on the injected water migration into the surrounding wells and their mutual location. On the basis of the settlement method the targeted program of geological and technical measures for regulating the work of the injection well stock was created and implemented by the example of the BV7 formation of the Uzhno-Vyintoiskoe oil field.

A New Method of Fall-Off Test in Water Injection Well in Tahe Oilfield

2013 ◽  
Vol 807-809 ◽  
pp. 2508-2513
Author(s):  
Qiang Wang ◽  
Wan Long Huang ◽  
Hai Min Xu
Keyword(s):  
Water Injection ◽  
Injection Well ◽  
Well Test ◽  
Well Bore ◽  
Residual Oil ◽  
Injection Wells ◽  
Oil Saturation ◽  
Tahe Oilfield ◽  
Fitting Method ◽  
Front Radius

In pressure drop well test of the clasolite water injection well of Tahe oilfield, through nonlinear automatic fitting method in the multi-complex reservoir mode for water injection wells, we got layer permeability, skin factor, well bore storage coefficient and flood front radius, and then we calculated the residual oil saturation distribution. Through the examples of the four wells of Tahe oilfield analyzed by our software, we found that the method is one of the most powerful analysis tools.

scholarly journals Experimental investigation on water-injected twin-screw compressor for fuel cell humidification

2012 ◽  
Vol 226 (12) ◽  
pp. 2925-2932 ◽  
Author(s):  
Talal Ous ◽  
Elvedin Mujic ◽  
Nikola Stosic
Keyword(s):  
Fuel Cell ◽  
Relative Humidity ◽  
Constant Pressure ◽  
Water Injection ◽  
Injection Rate ◽  
Fuel Cell Stack ◽  
Balance Of Plant ◽  
Air Supply ◽  
Twin Screw ◽  
Mass Flow Rates

Water injection in twin-screw compressors was examined in order to develop effective humidification and cooling schemes for fuel cell stacks as well as cooling for compressors. The temperature and the relative humidity of the air at suction and exhaust of the compressor were monitored under constant pressure and water injection rate and at variable compressor operating speeds. The experimental results showed that the relative humidity of the outlet air was increased by the water injection. The injection tends to have more effect on humidity at low operating speeds/mass flow rates. Further humidification can be achieved at higher speeds as a higher evaporation rate becomes available. It was also found that the rate of power produced by the fuel cell stack was higher than the rate used to run the compressor for the same amount of air supplied. The efficiency of the balance of plant was, therefore, higher when more air is delivered to the stack. However, this increase in the air supply needs additional subsystems for further humidification/cooling of the balance-of-plant system.

scholarly journals A Numerical Method for Computing Recovery of Oil By Hot Water Injection in a Radial System

1965 ◽  
Vol 5 (02) ◽  
pp. 131-140 ◽  
Author(s):  
K.P. Fournier
Keyword(s):  
Thermal Expansion ◽  
Oil Recovery ◽  
Viscosity Ratio ◽  
Water Injection ◽  
Injection Rate ◽  
Heat Losses ◽  
Hot Water ◽  
Radial System ◽  
System Equation ◽  
Finite Difference Equations

Abstract This report describes work on the problem of predicting oil recovery from a reservoir into which water is injected at a temperature higher than the reservoir temperature, taking into account effects of viscosity-ratio reduction, heat loss and thermal expansion. It includes the derivation of the equations involved, the finite difference equations used to solve the partial differential equation which models the system, and the results obtained using the IBM 1620 and 7090–1401 computers. Figures and tables show present results of this study of recovery as a function of reservoir thickness and injection rate. For a possible reservoir hot water flood in which 1,000 BWPD at 250F are injected, an additional 5 per cent recovery of oil in place in a swept 1,000-ft-radius reservoir is predicted after injection of one pore volume of water. INTRODUCTION The problem of predicting oil recovery from the injection of hot water has been discussed by several researchers.1–6,19 In no case has the problem of predicting heat losses been rigorously incorporated into the recovery and displacement calculation problem. Willman et al. describe an approximate method of such treatment.1 The calculation of heat losses in a reservoir and the corresponding temperature distribution while injecting a hot fluid has been attempted by several authors.7,8 In this report a method is presented to numerically predict the oil displacement by hot water in a radial system, taking into account the heat losses to adjacent strata, changes in viscosity ratio with temperature and the thermal-expansion effect for both oil and water. DERIVATION OF BASIC EQUATIONS We start with the familiar Buckley-Leverett9 equation for a radial system:*Equation 1 This can be written in the formEquation 2 This is sometimes referred to as the Lagrangian form of the displacement equation.

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