Production Monitoring of Multilateral Wells by Quantum Marker Systems

2022 ◽  
Author(s):  
Nadir Husein ◽  
Vishwajit Upadhye ◽  
Albina Viktorovna Drobot ◽  
Viacheslav Valeryevich Bolshakov ◽  
Anton Vitalyevich Buyanov
Keyword(s):  
Flow Rate ◽  
Oil Recovery ◽  
Capital Expenditure ◽  
Oil And Gas Industry ◽  
Effective Field ◽  
Dynamic Monitoring ◽  
Fluid Distribution ◽  
Field Development ◽  
Well Completion ◽  
Side Track

Abstract Reliable information about the inflow composition and distribution in a multilateral well is of great importance and an existing challenge in the oil and gas industry. In this paper, we present an innovative method for dynamic monitoring of inflow profile based on quantum marker technology in a multi-lateral well located in West Siberia. Marker systems were placed in the well during the well reconstruction by horizontal side tracking with the parent borehole remaining in production. This way of reconstruction allows development of the reservoir drainage area with a lateral hole and bringing the oil reserves from the parent borehole into production, which results in an increased flow rate and improved oil recovery rate. Placement of marker systems into parent borehole and side-track for fluid distribution monitoring allows to evaluate the flow rate from every borehole and estimate the effectiveness of performed well reconstruction. Marker systems are placed into the parent borehole as a downhole sub installed into the well completion string. For the side-track polymer-coated marked proppant was injected during hydraulic fracturing to place markers. The developed method was reliably used for an accurate and fast determination of the inflow distribution in a multi-lateral well which allows more efficient field development and also enabled us to provide effective solutions for following challenges: Providing tools for timely water cut diagnostics in multilateral wells and information for water shut-off method selection; Selecting the optimal well operating mode for effective field development and premature flooding prevention in one or both boreholes; Evaluating whether well construction was performed efficiently, and an increased production rate was achieved; Leading to a considerable economic savings in capital expenditure.

Experience of Using Continuous Production Surveillance Techniques in Multilateral Wells on Yuzhno-Priobskoye Field

2021 ◽  
Author(s):  
Nadir Husein ◽  
Vishwajit Upadhye ◽  
Igor Leonidovich Novikov ◽  
Albina Viktorovna Drobot ◽  
Viacheslav Valeryevich Bolshakov ◽  
...  
Keyword(s):  
Hydraulic Fracturing ◽  
Oil Recovery ◽  
Recovery Rate ◽  
Capital Expenditure ◽  
Continuous Production ◽  
Improved Oil Recovery ◽  
Well Completion ◽  
Multi Stage ◽  
Side Track ◽  
Horizontal Side

Abstract This paper deals with the case of using the production surveillance inflow tracer based method in one of multi-lateral wells located in the Yuzhno-Priobskoye field. Tracer systems were placed in the well during the well construction by horizontal side tracking, and multi-stage hydraulic fracturing (MSHF) was performed, with the parent borehole remaining in operation. This technology allows developing the reservoir drainage area with a lateral hole and bringing the oil reserves remaining in the parent borehole into production, which results in an increased well productivity and improved oil recovery rate. Tracer systems are placed into the parent borehole within a downhole sub installed into the well completion. Polymer-coated proppant packs were injected during multi-stage hydraulic fracturing to deliver the tracers to the side track lateral. Dynamic production profiling was done to aid into more efficient development of complex and heterogeneous reservoirs and improve of the productive reservoir sweep ratio during the construction of multilateral wells, which enabled us to address several key problems: Providing tools for waterflood diagnostics in multilateral wells and finding an easy water shutoff method for a certain interval Assessing the efficiency of multi-stage hydraulic fracturing and elaborating the optimal treatment design Selecting the optimal mode of the multilateral well operation to prevent premature flooding in one or more laterals Evaluating whether well construction was performed efficiently, and a higher production was achieved by side tracking. Currently, the proposed first-of-its-kind solution enables the operator to obtain a set of data that can help not only significantly improve the wells’ productivity and increase the oil recovery rate, but also lead to a considerable economic savings in capital expenditure.

scholarly journals A Hybrid Artificial Intelligence Model to Predict the Elastic Behavior of Sandstone Rocks

2019 ◽  
Vol 11 (19) ◽  
pp. 5283 ◽  
Author(s):  
Gowida ◽  
Moussa ◽  
Elkatatny ◽  
Ali
Keyword(s):  
Poisson’S Ratio ◽  
Accurate Determination ◽  
Oil And Gas Industry ◽  
Poisson's Ratio ◽  
Elastic Behavior ◽  
Percentage Error ◽  
Ann Model ◽  
Field Development ◽  
Well Completion

Rock mechanical properties play a key role in the optimization process of engineering practices in the oil and gas industry so that better field development decisions can be made. Estimation of these properties is central in well placement, drilling programs, and well completion design. The elastic behavior of rocks can be studied by determining two main parameters: Young’s modulus and Poisson’s ratio. Accurate determination of the Poisson’s ratio helps to estimate the in-situ horizontal stresses and in turn, avoid many critical problems which interrupt drilling operations, such as pipe sticking and wellbore instability issues. Accurate Poisson’s ratio values can be experimentally determined using retrieved core samples under simulated in-situ downhole conditions. However, this technique is time-consuming and economically ineffective, requiring the development of a more effective technique. This study has developed a new generalized model to estimate static Poisson’s ratio values of sandstone rocks using a supervised artificial neural network (ANN). The developed ANN model uses well log data such as bulk density and sonic log as the input parameters to target static Poisson’s ratio values as outputs. Subsequently, the developed ANN model was transformed into a more practical and easier to use white-box mode using an ANN-based empirical equation. Core data (692 data points) and their corresponding petrophysical data were used to train and test the ANN model. The self-adaptive differential evolution (SADE) algorithm was used to fine-tune the parameters of the ANN model to obtain the most accurate results in terms of the highest correlation coefficient (R) and the lowest mean absolute percentage error (MAPE). The results obtained from the optimized ANN model show an excellent agreement with the laboratory measured static Poisson’s ratio, confirming the high accuracy of the developed model. A comparison of the developed ANN-based empirical correlation with the previously developed approaches demonstrates the superiority of the developed correlation in predicting static Poisson’s ratio values with the highest R and the lowest MAPE. The developed correlation performs in a manner far superior to other approaches when validated against unseen field data. The developed ANN-based mathematical model can be used as a robust tool to estimate static Poisson’s ratio without the need to run the ANN model.

Design of an Economical Polymer Flood Pilot Addressing Field Development Uncertainties in the Sabriyah Upper Burgan Reservoir of North Kuwait

2021 ◽  
Author(s):  
Mohammed T. Al-Murayri ◽  
Dawood Kamal ◽  
Najres Al-Mahmeed ◽  
Anfal Al Kharji ◽  
Hadeel Baroon ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Polymer Flooding ◽  
Mobility Control ◽  
Field Development ◽  
Reservoir Volume ◽  
Polymer Flood ◽  
Incremental Oil Recovery ◽  
Commercial Size

Abstract The Sabriyah Upper Burgan is a major oil reservoir in North Kuwait with high oil saturation and is currently considered for mobility control via polymer flooding. Although there is high confidence in the selected technology, there are technological and geologic challenges that must be understood to transition towards phased commercial field development. Engineering and geologic screening suggested that chemical flood technologies were superior to either miscible gas or waterflood technologies. Of the chemical flood technologies, mobility control flooding was considered the best choice due to available water ion composition and total dissolved solids (TDS). Evaluation of operational and economic considerations were instrumental in recommending mobility control polymer flooding for pilot testing. Laboratory selected acceptable polymer for use with coreflood incremental oil recovery being up to 9% OOIP. Numerical simulation recommended two commercial size pilots, a 3-pattern and a 5-pattern of irregular five spots, with forecast incremental oil recovery factors of 5.6% OOIP over waterflood. Geologic uncertainty is the greatest challenge in the oil and gas industry, which is exacerbated with any EOR project. Screening of the Upper Burgan reservoirs indicates that UB4 channel sands are the best candidates for EOR technologies. Reservoir quality is excellent and there is sufficient reservoir volume in the northwest quadrant of the field to justify not only a pilot but also future expansion. There is a limited edge water drive of unknown strength that will need to be assessed. The channel facies sandstones have porosities of +25%, permeabilities in the Darcy range, and initial oil saturations of +90%. Pore volume (PV) of the two recommended pilot varies from 29 to 45 million barrels. A total of 0.7 PV of polymer is expected to be injected in 5.6 and 7.9 years for the 3-pattern pilot and the 5-pattern pilot, respectively, with a water drive flush to follow for an additional 5 to 7 years. Incremental cost per incremental barrel of oil of a mobility control polymer flood which includes OPEX and CAPEX costs is $20 (USD). This paper evaluates the (commercial size) pilot design and addresses field development uncertainties.

Experimental Study of Pipe Pulling Through Settled Barite

2019 ◽  
Author(s):  
Ali Taghipour ◽  
Torbjørn Vrålstad ◽  
Ragnhild Skorpa ◽  
Mohammad Hossain Bhuiyan ◽  
Jan David Ytrehus ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Drilling Fluid ◽  
Gas Production ◽  
Solid Particles ◽  
Cement Slurry ◽  
Oil And Gas Production ◽  
Field Development ◽  
Steel Pipes ◽  
Well Completion ◽  
Side Track

Abstract Wells are essential in oil and gas production and construction of them is one of the main cost drivers for field development. It is normally needed to drill and construct new wells from existing fields during most of the production time. In order to reduce costs one can re-use parts of existing wells when they are no longer efficient. This is done in offshore fields also when there is limitation for new wells due to capacity of the subsea template. Through tubing drilling is a method to drill a side track through the wellbore tubulars. However, this will normally result in a smaller and less effective well completion. Removing parts of the casing section and drill a larger size sidetrack is an option to provide a new full-size wellbore. Removing the 9 5/8” casing through the settled particle in the annulus can be challenging. The wellbore annulus is normally filled with old drilling fluid, displacing fluid and/or cement slurry. The solid particles of these annular fluids are settled during years of shut-in and make it difficult to move the casing sections. There are several techniques for pulling the casing section, but there is a lack of knowledge of some of the key mechanism causing the resistance in these operations. In order to study and address the dominating effects in these operations, down-scaled laboratory tests are performed. The experiments reported here are performed by pulling steel pipes through the settled barite in the annulus. The pipes used in the tests are down-scaled from typical casing sizes with and without collars. The barite slurry compacted inside the annulus have different hydrostatic and pore pressures. When the pipe is pulled the required mechanical force is measured. Results show that the single most significant factor causing resistance when pulling the tubulars is the collars outside the pipe. Furthermore, it is identified that the pore pressure improves the mobility of the settled particle around the collar. In total these results provide improved understanding on the dominating factors during pulling pipes from a packed annulus.

Increasing Reservoir Productivity at Yuzhno Vyintoyskoye Field, Western Siberia

2021 ◽  
Author(s):  
Marat Dulkarnaev ◽  
Nadir Husein ◽  
Evgeny Malyavko ◽  
Vladimir Liss ◽  
Viacheslav Bolshakov ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Western Siberia ◽  
Oil And Gas ◽  
Flow Simulation ◽  
Horizontal Wells ◽  
Oil And Gas Industry ◽  
Economic Conditions ◽  
Gas Industry ◽  
Field Development ◽  
The One

Abstract The new economic conditions characterised by the instability in the global oil and gas industry push market players to search for profitable and efficient ways of developing oil and gas deposits. One of the key opportunities is Enhanced Oil Recovery projects in hard-to-recover reservoirs and formations. When planning the entire scope of development operations, well interventions and surveys, it is important to follow a strategy that would help successfully overcome the geological and engineering challenges facing the operators. In this project, a geological feasibility study of the field development management was conducted with regards to the one formation of the Yuzhno-Vyintoyskoye field based on the data obtained using marker-based production surveillance in horizontal wells and flow simulation.

scholarly journals Use of Smart Controls in Intelligent Well Completion to Optimize Oil & Gas Recovery

2019 ◽  
pp. 1-14
Author(s):  
Austin Afuekwe ◽  
Kelani Bello
Keyword(s):  
Crude Oil ◽  
Oil Recovery ◽  
Oil And Gas ◽  
New Technology ◽  
Oil And Gas Industry ◽  
Water Production ◽  
Monitoring And Control ◽  
Reactive Control ◽  
Well Completion ◽  
Reservoir Simulator

For the past few years, the oil and gas industry has faced several economic, geographic and technical challenges largely due to decline in crude oil prices and market volatility. In the quest to address some of these challenges to accelerate production and subsequently maximize ultimate recovery, operators are limited to remote hydraulic and electro-hydraulic monitoring and control of safety valves providing the means of obtaining downhole production data which demands periodic well intervention-based techniques with risk of loss of associated tools. This has highlighted the need for companies to adopt new technology to take advantage of low crude oil price environment, optimizing recovery without interventions and with minimal production interruption. One of the recent improvements in production technologies which can remedy these problems having unique capabilities to do so is the Intelligent Well Completion (IWC) technology. In this paper the utilization of IWC to optimize oil recovery was evaluated. The use of a reservoir simulator, the Schlumberger ECLIPSE-100 simulator, was employed to model an intelligent well. Case study simulations were performed for an active bottom-water drive. Modeling of the Intelligent Well Inflow Control Devices (ICDs) and downhole sensors for the multilaterals was achieved using the Multi-Segment Well model. Optimal IWC technology combination for maximum hydrocarbon recovery and minimal water production was determined using the reactive control strategy (RCS) which indicated a drastic reduction of about 52.1% in water production with a slight drop of 1.5% in field oil efficiency (FOE). The simulation results obtained clearly showed that the utilization of intelligent well-ICDs in Production wells can significantly increase the cumulative oil production and reduce water production.

scholarly journals Practical CO2—WAG Field Operational Designs Using Hybrid Numerical-Machine-Learning Approaches

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1055
Author(s):  
Qian Sun ◽  
William Ampomah ◽  
Junyu You ◽  
Martha Cather ◽  
Robert Balch
Keyword(s):  
Machine Learning ◽  
Oil Recovery ◽  
History Matching ◽  
Optimization Problems ◽  
Learning Technologies ◽  
Petroleum Engineering ◽  
Support Vector ◽  
Learning Approaches ◽  
Field Development ◽  
Proxy Models

Machine-learning technologies have exhibited robust competences in solving many petroleum engineering problems. The accurate predictivity and fast computational speed enable a large volume of time-consuming engineering processes such as history-matching and field development optimization. The Southwest Regional Partnership on Carbon Sequestration (SWP) project desires rigorous history-matching and multi-objective optimization processes, which fits the superiorities of the machine-learning approaches. Although the machine-learning proxy models are trained and validated before imposing to solve practical problems, the error margin would essentially introduce uncertainties to the results. In this paper, a hybrid numerical machine-learning workflow solving various optimization problems is presented. By coupling the expert machine-learning proxies with a global optimizer, the workflow successfully solves the history-matching and CO2 water alternative gas (WAG) design problem with low computational overheads. The history-matching work considers the heterogeneities of multiphase relative characteristics, and the CO2-WAG injection design takes multiple techno-economic objective functions into accounts. This work trained an expert response surface, a support vector machine, and a multi-layer neural network as proxy models to effectively learn the high-dimensional nonlinear data structure. The proposed workflow suggests revisiting the high-fidelity numerical simulator for validation purposes. The experience gained from this work would provide valuable guiding insights to similar CO2 enhanced oil recovery (EOR) projects.

Simultaneous Measuring Method for Both Volumetric Flow Rates of Air-Water Mixture Using a Turbine Flowmeter

1996 ◽  
Vol 118 (1) ◽  
pp. 29-35 ◽  
Author(s):  
K. Minemura ◽  
K. Egashira ◽  
K. Ihara ◽  
H. Furuta ◽  
K. Yamamoto
Keyword(s):  
Pressure Drop ◽  
Flow Rate ◽  
Volumetric Flow Rate ◽  
Oil Field ◽  
Liquid Density ◽  
Water Mixture ◽  
Rotor Speed ◽  
Flow Rates ◽  
Field Development ◽  
Turbine Flowmeter

A turbine flowmeter is employed in this study in connection with offshore oil field development, in order to measure simultaneously both the volumetric flow rates of air-water two-phase mixture. Though a conventional turbine flowmeter is generally used to measure the single-phase volumetric flow rate by obtaining the rotational rotor speed, the method proposed additionally reads the pressure drop across the meter. After the pressure drop and rotor speed measured are correlated as functions of the volumetric flow ratio of the air to the whole fluid and the total volumetric flow rate, both the flow rates are iteratively evaluated with the functions on the premise that the liquid density is known. The evaluated flow rates are confirmed to have adequate accuracy, and thus the applicability of the method to oil fields.

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