An Efficient Workflow for Production Allocation During Water Flooding

2016 ◽  
Vol 139 (3) ◽  
Author(s):  
Vahid Azamipour ◽  
Mehdi Assareh ◽  
Mohammad Reza Dehghani ◽  
Georg M. Mittermeir
Keyword(s):  
Objective Function ◽  
Water Injection ◽  
Oil Production ◽  
Injection Rate ◽  
Coarse Grid ◽  
Recovery Factor ◽  
Total Water ◽  
Production Schedule ◽  
Production Rates ◽  
Total Oil

This paper presents an efficient production optimization scheme for an oil reservoir undergoing water injection by optimizing the production rate for each well. In this approach, an adaptive version of simulated annealing (ASA) is used in two steps. The optimization variables updating in the first stage is associated with a coarse grid model. In the second step, the fine grid model is used to provide more details in final solution search. The proposed method is formulated as a constrained optimization problem defining a desired objective function and a set of existing field/facility constraints. The use of polytope in the ASA ensures the best solution in each iteration. The objective function is based on net present value (NPV). The initial oil production rates for each well come from capacity and property of each well. The coarse grid block model is generated based on average horizon permeability. The proposed optimization workflow was implemented for a field sector model. The results showed that the improved rates optimize the total oil production. The optimization of oil production rates and total water injection rate leads to increase in the total oil production from 315.616 MSm3 (our initial guess) to 440.184 MSm3, and the recovery factor is increased to 26.37%; however, the initial rates are much higher than the optimized rates. Beside this, the recovery factor of optimized production schedule with optimized total injection rate is 3.26% larger than the initial production schedule with optimized total water injection rate.

Integrated Dynamic Synthesis as Key Success to Sustain Oil Production in Mahakam: Case Water Flooding Project in Handil Field

2021 ◽  
Author(s):  
A. H. Surbakti
Keyword(s):  
Reservoir Simulation ◽  
Water Injection ◽  
Oil Production ◽  
Recovery Factor ◽  
Water Flooding ◽  
Sweet Spot ◽  
Main Zone ◽  
Spot Area ◽  
Dynamic Synthesis ◽  
Main Challenge

The Handil field is located in the Kutai Basin with an anticlinal structure consisting of a vertically stacked reservoirs deposited in a fluvial-deltaic environment. The field has been producing since 1974 under active aquifer drive followed by peripheral water injection which resulting in a high recovery factor of oil production. Cumulative oil production is more than 900 MMbbls and currently the field is still producing at 15000 bopd. The Handil Main zone is the main contributor that accounts for 60% of the Handil Field production and based on the results of new wells drilling, there is still potential of the remaining oil accumulations. Therefore, an integrated subsurface study is needed to further increase recovery in the Handil Main zone. This paper will discuss the process used to locate unswept oil in the high water cut reservoir to extend the water flood project. Waterflooding became an important part of the Handil’s development strategy to maximize oil recovery and to maintain oil reservoir pressure, as more and more fields are matured as part of their production life cycle. The main challenge is to identify area of unsweep oil that are affected by water injection activity. Understanding the reservoir behavior of the water injection sweep characteristic can significantly improve the understanding of the distribution of unswept oil in the reservoir. A robust integrated methodology was developed to identify unswept oil area by integrating Static- dynamic synthesis, 3D static model, production history, reservoir connectivity, recent well logs data and reservoir simulation. Multiple QC of oil sweet spot are done by comparing the sweet spot area of dynamic synthesis with reservoir simulation. Detailed well correlation were performed to identify the optimum water injector placement to improve the recovery factor. The results of the integrated dynamic synthesis are used to identify the sweet spot area and the optimum well injector location that will be used for the water flooding development project to be executed in 2022. The results of the study will sustain Mahakam production in the future.

scholarly journals Simulation Study of Allied In-Situ Injection and Production for Enhancing Shale Oil Recovery and CO2 Emission Control

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3961
Author(s):  
Haiyang Yu ◽  
Songchao Qi ◽  
Zhewei Chen ◽  
Shiqing Cheng ◽  
Qichao Xie ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Co2 Emission ◽  
Gas Injection ◽  
Water Injection ◽  
Oil Production ◽  
Injection Rate ◽  
Oil Reservoirs ◽  
Shale Oil ◽  
Shale Oil Reservoirs

The global greenhouse effect makes carbon dioxide (CO2) emission reduction an important task for the world, however, CO2 can be used as injected fluid to develop shale oil reservoirs. Conventional water injection and gas injection methods cannot achieve desired development results for shale oil reservoirs. Poor injection capacity exists in water injection development, while the time of gas breakthrough is early and gas channeling is serious for gas injection development. These problems will lead to insufficient formation energy supplement, rapid energy depletion, and low ultimate recovery. Gas injection huff and puff (huff-n-puff), as another improved method, is applied to develop shale oil reservoirs. However, the shortcomings of huff-n-puff are the low sweep efficiency and poor performance for the late development of oilfields. Therefore, this paper adopts firstly the method of Allied In-Situ Injection and Production (AIIP) combined with CO2 huff-n-puff to develop shale oil reservoirs. Based on the data of Shengli Oilfield, a dual-porosity and dual-permeability model in reservoir-scale is established. Compared with traditional CO2 huff-n-puff and depletion method, the cumulative oil production of AIIP combined with CO2 huff-n-puff increases by 13,077 and 17,450 m3 respectively, indicating that this method has a good application prospect. Sensitivity analyses are further conducted, including injection volume, injection rate, soaking time, fracture half-length, and fracture spacing. The results indicate that injection volume, not injection rate, is the important factor affecting the performance. With the increment of fracture half-length and the decrement of fracture spacing, the cumulative oil production of the single well increases, but the incremental rate slows down gradually. With the increment of soaking time, cumulative oil production increases first and then decreases. These parameters have a relatively suitable value, which makes the performance better. This new method can not only enhance shale oil recovery, but also can be used for CO2 emission control.

A Field Pilot of Waterflooding Conformance Control in Tight Oil Reservoir with Biotechnology

2021 ◽  
Author(s):  
Songyuan Liu ◽  
Xiaochun Jin ◽  
Deji Liu ◽  
Hao Xu ◽  
Lidong Zhang ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Water Injection ◽  
Vertical Direction ◽  
Cost Effective ◽  
Injection Rate ◽  
Recovery Factor ◽  
Tight Oil ◽  
Index Test ◽  
Indigenous Bacteria ◽  
Water Cut

Abstract Traditional Microbial Enhanced Oil Recovery (MEOR) technology assumes the oil recovery is increased by the biosurfactant generating by the subsurface bacteria. However, we identified that increased recovery factor is mainly contributed by stimulating the indigenous bacteria to plug the preferred waterflooding channels, which was proved at laboratory and some high-permeable oilfield, but never implemented in the waterflooding of tight oilfield. This paper presents a comprehensive study on Bio-diversion technique by stimulating indigenous bacteria covering lab research and filed operation lasting 18 months. The lab research comprised: (1) feasibility research using modified recipe and field sample on the stimulation of indigenous microorganisms; and (2) Evaluation of effectiveness of the stimulation based on lab results. A field pilot, consisting of 10 injectors, 10 producers, injecting and producing from multi-zones, reservoir temperature is about 160 F, permeabilities range from 30 md to over 100 md, daily water injection rate is about 2,000 BWPD, pre-treatment water cut is over 90%. It is observed that the water cut has decreased from 98% to 80% gradually (3-6 months after injection). Besides, the water injection index test indicates that the injection profile becomes more evenly after 9 months of microbial nutrient injection because the stimulated bacteria reduce the permeability of more permeable zones and reduce the permeability heterogeneity in the vertical direction. Sharing the field results with the industry may inspire the operators to consider one alternative environmentally friendly and cost-effective approach to increase the recovery factor of tight oil reservoirs. From the technical viewpoint, the field pilot proves that the major mechanisms of MEOR is sweeping the unswept oil by injecting the microbial nutrient to the reservoir to stimulate the indigenous bacteria to block the preferred waterflooding channels.

Development of World-Class Oil Production and Water Injection Rate and High Ultimate-Recovery Wells in Deepwater Turbidites--Bonga Example

2009 ◽  
Vol 24 (02) ◽  
pp. 293-302
Author(s):  
Solomon O. Inikori ◽  
Bert Coxe ◽  
Ebenezer Ageh ◽  
Jaap W. Van der Bok
Keyword(s):  
Water Injection ◽  
Oil Production ◽  
Injection Rate ◽  
World Class

scholarly journals New proxy models for predicting oil recovery factor in waterflooded heterogeneous reservoirs

2021 ◽  
Vol 11 (3) ◽  
pp. 1443-1459
Author(s):  
Mohamed Al-Jifri ◽  
Hazim Al-Attar ◽  
Fathi Boukadi
Keyword(s):  
Statistical Study ◽  
Water Injection ◽  
Injection Rate ◽  
Recovery Factor ◽  
Data Sets ◽  
Data Set ◽  
Percent Difference ◽  
Permeability Anisotropy ◽  
Permeability Variation ◽  
Reduced Forms

AbstractTo predict the recovery factor (RF) in waterflooded layered oil reservoirs, two empirical relationships were derived. Both correlations use four independent variables. These are reservoir heterogeneity (characterized by permeability variation coefficient), permeability anisotropy (ratio of vertical to horizontal permeability), viscosity of the injected water, and water injection rate. One of the correlations estimates RF at water breakthrough time (RFBT) and the other evaluates RF at the end of project (RFEOP). Each correlation comes in an expanded form with more parameters and a reduced form with fewer parameters. Both models are based on the global linear model. Eclipse black-oil simulation was used to determine RF for generic reservoirs with different combinations of permeability variation, permeability anisotropy, injected water viscosities, and water injection rates. A total of 192 data sets have been generated. Out of these, 144 data sets (about 75% of the generated sets) were used for model development and 48 data sets (about 25% of the generated sets) were used for model testing and validation. The expanded forms of the new developed correlations gave reliable estimates of RFBT and RFEOP with absolute average percent difference (AAPCD) of 6.9 and 1.02, respectively. The reduced forms yielded slightly higher AAPCDs of 8.30 and 1.04, respectively. When tested against 48 simulation-generated data sets, the expanded forms yielded excellent fits for RFBT and RFEOP with AAPCDs of 14 and 6.5, respectively. The reduced forms showed comparable fit with AAPCDs of 16.9 and 6.70, respectively. The highest RFEOP of 50.6% was achieved for a generic reservoir with a permeability variation in V = 0.1 and a permeability anisotropy of kz/kx = 1.0. This particular reservoir needs to be waterflooded using a water viscosity of µw = 1.0 cp and a water injection rate of qi = 10,000 bpd. Finally, when tested against the Guthrie–Greenberger and the API statistical study, using a single field data set, the proposed correlations gave higher absolute percent difference of 22.9 and 22.7 compared to 0.758 and 19.2 for Guthrie–Greenberger and the API statistical study, respectively.

scholarly journals Developing a new technique for the simultaneous optimization of both segmented time and injection rate for water flooding reservoirs: An analysis of Shengli Oilfield XIN-42 reservoir block

2020 ◽  
Vol 38 (6) ◽  
pp. 2356-2369
Author(s):  
Yinfei Ma ◽  
Anfeng Shi ◽  
Xiaohong Wang ◽  
Baoguo Tan ◽  
Hongxia Sun
Keyword(s):  
Net Present Value ◽  
Water Injection ◽  
Oil Production ◽  
Adjustment Costs ◽  
Injection Rate ◽  
Production Optimization ◽  
Simultaneous Optimization ◽  
Water Flooding ◽  
Present Value ◽  
Oil Production Optimization

The adjustment and control of the water injection rate is a commonly used method for increasing the cumulative oil production of waterflooded reservoirs. This article studies the production optimization problem under the condition of a fixed total water injection rate. The production process is divided into several segments. Considering the correlation between the segment’s time intervals and the well’s injection rate distribution, a simultaneous optimization of both segmented time and injection rate is proposed for enhancing net present value. Both empirical simulations and field application demonstrate that the suggested methods produce the highest increase in net present value – of approximately 13% and 10%, respectively – and significantly improve water flooding efficiency compared to other conventional schemes, such as segmented oil production optimization, cumulative oil production optimization and Bang-Bang control. The proposed methods under a 2-segment division increase oil production efficiency and greatly reduce adjustment costs.

Water-Injection Optimization for a Complex Fluvial Heavy-Oil Reservoir by Integrating Geological, Seismic, and Production Data

2009 ◽  
Vol 12 (06) ◽  
pp. 865-878 ◽  
Author(s):  
Xin Feng ◽  
Xian-Huan Wen ◽  
Bo Li ◽  
Ming Liu ◽  
Dengen Zhou ◽  
...  
Keyword(s):  
Heavy Oil ◽  
Water Injection ◽  
Oil Production ◽  
Injection Rate ◽  
Production Data ◽  
Oil Reservoir ◽  
Reservoir Pressure ◽  
Channel Geometry ◽  
Heavy Oil Reservoir ◽  
Complex Channel

Summary BZ25-1s field in Bohai Bay, China, is characterized as a complex channelized fluvial reservoir in which small meandering channels were deposited at different geological times stacking and cross cutting each other. There are many isolated small reservoir systems following channel distributions. Early production showed steep pressure and production decline. Quick implementation of water injection was needed to arrest the fast production decline and to stabilize reservoir pressure. While designing the water-injection plan, we faced a number of challenges, such as high oil viscosity (˜200 cp), strong heterogeneity, poor reservoir connectivity, complex channel geometry, and irregular well patterns. A workflow integrating geological, well-log, seismic, and dynamic production data was developed to optimize a water injection plan for this field after a short production history. Focuses of this workflow are the selection of injection wells (converted from existing producers), timing of water injection, and the optimization of injection rates. Following the workflow, the optimal water-injection design for the areas around Platforms D and E was developed and quickly implemented within the first year of production. We started with a relatively small water-injection rate and gradually increased the injection rate to avoid the fast water breakthrough and yet to limit the pressure-decline rate. The responses from the water injection were very positive and resulted in stable reservoir pressure and increase of oil production. Before water injection, the production-decline rates were 26 and 47% in Platforms D and E, respectively. After 1 year of water injection, oil-production-decline rates in these two platforms were reduced to 19 and 14%, respectively. The responses of water injection for different well groups were analyzed in a timely fashion and adjustments to injection/production strategies were implemented accordingly. New information revealed from the water-injection response analysis was used to update the geological model to reduce the model uncertainty, as well as to adjust the water-injection strategies for better sweep efficiency. Our experiences showed that such dynamic adjustment of injection and production schedule is very important to achieve better water-injection efficiency for this heavy-oil reservoir with complex channel geometry.

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.

Sign in / Sign up

Export Citation Format

Share Document