Expansion of Data Analytics for Optimizing Steamflood In Mukhaizna Heavy Oil Field

2021 ◽  
Author(s):  
Mohammed Al Asimi ◽  
Nasar Al Qasabi ◽  
Duc Le ◽  
Yuchen Zhang ◽  
Di Zhu ◽  
...  
Keyword(s):  
Heavy Oil ◽  
Data Analytics ◽  
Oil Production ◽  
Steam Injection ◽  
Lessons Learned ◽  
Oil Field ◽  
Production Performance ◽  
Optimization Process ◽  
Successful Implementation ◽  
Full Field

Abstract After successful implementation of data analytics for steamflood optimization at the Mukhaizna heavy oil field in Oman late 2018, Occidental expanded the project to two additional areas with a total of 626 wells in 2019, followed by full field coverage of more than 3,200 wells in 2020. In 2019, two separate low-fidelity proxy models were built to model the two pilot areas. The models were updated with more features to account for additional reservoir phenomena and a larger scope. On the proxy engine side, speed and robustness were improved, resulting in reduced CPU processing time and lower cost. Because of advancements in software programing and the pilots’ encouraging production performance, full-field coverage was accelerated so the model could support the efforts in optimizing steam injection during the 2020 OPEC+ production cut, not only to comply with allotted quotas, but also to allocate the resources optimally, especially the costly steam. Good improvements have been observed in overall steamflood performance, the models’ capabilities, and the optimization workflow. The steam/oil ratio has been reduced through the increase in oil production in both expanded study areas while keeping the total steam injection volume constant. Overall field steam utilization was improved both during the 2020 OPEC+ production cuts and during the production ramp-up stage afterward. With the continuous improvement in supporting tools and scripts, most of the steam optimization process steps were automated, from preparing, checking, and formatting input data to analyzing, validating, and visualizing the model outputs. Another result of these improvements was the development of a user-friendly web application to manage the model workflow efficiently. This web app greatly improved the process of case submittals, including data preparation and QC, running models (history matching and forecasting), as well as visualization of the entire workflow. In terms of optimization workflow, these improvements resulted in less time spent by the field optimization engineer in updating, refreshing, and generating new model recommendations. It also helped reduce the time spent by the reservoir management team (RMT) to test and validate the new ideas before field implementation. This paper will describe the improvements in the proxy model and the overall optimization process, show the observed oil production increases, and discuss the challenges faced and the lessons learned.

Inflow Performance of a Cyclic-Steam-Stimulated Horizontal Well Under the Influence of Gravity Drainage

SPE Journal ◽  
2011 ◽  
Vol 16 (03) ◽  
pp. 494-502 ◽  
Author(s):  
Z.. Wu ◽  
S.. Vasantharajan ◽  
M.. El-Mandouh ◽  
P.V.. V. Suryanarayana
Keyword(s):  
Heavy Oil ◽  
Horizontal Well ◽  
Oil Production ◽  
Steam Injection ◽  
Oil Field ◽  
Gravity Drainage ◽  
Attractive Alternative ◽  
Underlying Assumption ◽  
Heated Oil ◽  
Condensed Water

Summary In this paper, we present a new, semianalytical gravity-drainage model to predict the oil production of a cyclic-steam-stimulated horizontal well. The underlying assumption is that the cyclic steam injection creates a cylindrical steam chamber in the upper area of the well. Condensed water and heated oil in the chamber are driven by gravity and pressure drawdown toward the well. The heat loss during the soak period and during oil production is estimated under the assumption of vertical and radial conduction. The average temperature change in the chamber during the cycle is calculated using a semianalytical expression. Nonlinear, second-order ordinary differential equations are derived to describe the pressure distribution caused by the two-phase flow in the wellbore. A simple iteration scheme is proposed to solve these equations. The influx of heated oil and condensed water into the horizontal wellbore is calculated under the assumption of steady-state radial flow. The solution from the semianalytical formulation is compared against the results from a commercial thermal simulator for an example problem. It is shown that the model results are in good agreement with those obtained from reservoir simulation. Sensitivity studies for optimization of wellbore length, gravity drainage, bottomhole pressure, and steam-injection rate are conducted with the model. Results indicate that the proposed model can be used in the optimization of individual-well performance in cyclic-steam-injection heavy-oil development. The semianalytical thermal model presented in this work can offer an attractive alternative to numerical simulation for planning heavy-oil field development.

An Australian first initiative to re-develop the first commercial onshore oilfield into a CO2 miscible-EOR project

2019 ◽  
Vol 59 (1) ◽  
pp. 179
Author(s):  
Stephanie Barakat ◽  
Bob Cook ◽  
Karine D'Amore ◽  
Alberto Diaz ◽  
Andres Bracho
Keyword(s):  
Oil Recovery ◽  
Dynamic Modelling ◽  
Oil Production ◽  
Simulation Modelling ◽  
Oil Field ◽  
Optimal Time ◽  
Successful Implementation ◽  
Full Field ◽  
Execution Phase ◽  
Reservoir Simulator

The Moonie onshore oil field discovered in 1961, was the first commercial oil discovery in Australia. The field was purchased by Bridgeport Energy Limited (BEL) from Santos in late 2015. An Australian first initiative by BEL is to enhance oil production from the field using tertiary recovery CO2 miscible flood to maximise field oil recovery. The process involves an evaluation of well injection strategies for a miscible displacement process using reservoir simulation modelling. In addition, the project jointly addresses community concerns regarding the rise in greenhouse gas emissions by sourcing 60000–120000 tonnes/annum of CO2 from a nearby power station and/or an ethanol plant. Justified by laboratory experiments and reservoir compositional simulations, BEL’s project timeline to implement a CO2-enhanced oil recovery (EOR) pilot could start from 2020 followed by a 2–3-year full field oil production acceleration project if additional CO2 can be sourced. Based on incremental recovery and operational consideration, an injection well in the southern end of the field surrounded by six existing producers has been selected as a pilot flood. Positive indicative economics are achieved by the efficient displacement with CO2 of 8000 scf/bbl of incremental oil. Full field dynamic modelling predicts a further 8% oil recovery factor by injecting 60 Bcf of CO2 over five years, which could store in excess of three million tonnes of CO2. For the pilot, more than 90% of the injected CO2 will remain in the Precipice sandstone reservoir. However, the efficiency and viability of a CO2-EOR project is subject to successful implementation of the miscibility modelling, logistics and injection strategy and uncertainty quantification. To propel the project into the execution phase a fast-multiphase reservoir simulator has been implemented to complete a probabilistic range of results in optimal time.

Unlocking By-Passed Oil with Autonomous Inflow Control Devices Through an Integrated Approach

2021 ◽  
Author(s):  
Pawan Agrawal ◽  
Sharifa Yousif ◽  
Ahmed Shokry ◽  
Talha Saqib ◽  
Osama Keshtta ◽  
...  
Keyword(s):  
Continuous Production ◽  
Oil Production ◽  
Gas Production ◽  
Oil Field ◽  
Production Performance ◽  
Fluid Distribution ◽  
Flow Profile ◽  
Horizontal Drain ◽  
Control Devices

Abstract In a giant offshore UAE carbonate oil field, challenges related to advanced maturity, presence of a huge gas-cap and reservoir heterogeneities have impacted production performance. More than 30% of oil producers are closed due to gas front advance and this percentage is increasing with time. The viability of future developments is highly impacted by lower completion design and ways to limit gas breakthrough. Autonomous inflow-control devices (AICD's) are seen as a viable lower completion method to mitigate gas production while allowing oil production, but their effect on pressure drawdown must be carefully accounted for, in a context of particularly high export pressure. A first AICD completion was tested in 2020, after a careful selection amongst high-GOR wells and a diagnosis of underlying gas production mechanisms. The selected pilot is an open-hole horizontal drain closed due to high GOR. Its production profile was investigated through a baseline production log. Several AICD designs were simulated using a nodal analysis model to account for the export pressure. Reservoir simulation was used to evaluate the long-term performance of short-listed scenarios. The integrated process involved all disciplines, from geology, reservoir engineering, petrophysics, to petroleum and completion engineering. In the finally selected design, only the high-permeability heel part of the horizontal drain was covered by AICDs, whereas the rest was completed with pre-perforated liner intervals, separated with swell packers. It was considered that a balance between gas isolation and pressure draw-down reduction had to be found to ensure production viability for such pilot evaluation. Subsequent to the re-completion, the well could be produced at low GOR, and a second production log confirmed the effectiveness of AICDs in isolating free gas production, while enhancing healthy oil production from the deeper part of the drain. Continuous production monitoring, and other flow profile surveys, will complete the evaluation of AICD effectiveness and its adaptability to evolving pressure and fluid distribution within the reservoir. Several lessons will be learnt from this first AICD pilot, particularly related to the criticality of fully integrated subsurface understanding, evaluation, and completion design studies. The use of AICD technology appears promising for retrofit solutions in high-GOR inactive strings, prolonging well life and increasing reserves. Regarding newly drilled wells, dedicated efforts are underway to associate this technology with enhanced reservoir evaluation methods, allowing to directly design the lower completion based on diagnosed reservoir heterogeneities. Reduced export pressure and artificial lift will feature in future field development phases, and offer the flexibility to extend the use of AICD's. The current technology evaluation phases are however crucial in the definition of such technology deployments and the confirmation of their long-term viability.

Feasibility study of time-lapse seismic monitoring of EOR with steam injection in a heavy oil field

2009 ◽  
Author(s):  
Sung Yuh ◽  
Mickaele Le Ravalec-Dupin ◽  
Christian Hubans ◽  
Pierre-Olivier Lys ◽  
David Jean Foulon
Keyword(s):  
Feasibility Study ◽  
Heavy Oil ◽  
Time Lapse ◽  
Steam Injection ◽  
Seismic Monitoring ◽  
Oil Field

Surface Facilities for Thermal EOR Projects: Extra Heavy Oil

2018 ◽  
Author(s):  
Gilberto Peña Villegas ◽  
María del Carmen Echeverrías
Keyword(s):  
Heavy Oil ◽  
Steam Injection ◽  
Oil Field ◽  
Steam Flooding ◽  
Facilities Design ◽  
Integrated Project ◽  
Integrated Study ◽  
Global Project ◽  
New Facilities

A Giant Heavy Oil Field requires extending and maintaining the production plateau during a continuous period of more than 30 years. In order to increase the revenues of the global project, the construction of Upgrader plant is always considered. Cold production conditions are first, the project has estimated between 10-8% of the STOIIP obtained through cold production but it would not be enough to extend the production plateau. Therefore, later on it will be necessary to apply thermal EOR techniques, as: • Steam Injection: 1-CSS + Steam Flooding, 2-SAGD or HASD • In-situ combustion Aim for this integrated study was to visualize the new facilities design and modification on the exiting cold production facilities to manage the hot production (investments) in function of reservoir/production requirements. The benefit of this integrated study is to value the additional investments in surface facilities required under thermal EOR production to get the global integrated project evaluation.

scholarly journals A fishtail well design for cyclic steam injection—A case study from Yarega heavy oil field in Russia

2019 ◽  
Vol 7 (6) ◽  
pp. 2437-2455 ◽  
Author(s):  
German A. Abzaletdinov ◽  
Temitope Ajayi ◽  
Youssuf A. Elnoamany ◽  
Sergey Durkin ◽  
Ipsita Gupta
Keyword(s):  
Heavy Oil ◽  
Steam Injection ◽  
Oil Field ◽  
Well Design

A New Artificial Intelligence Method to Predict Water Flooding Performance in Layered Reservoir

2021 ◽  
Author(s):  
Cunliang Chen ◽  
Xiaodong Han ◽  
Wei Zhang ◽  
Yanhui Zhang ◽  
Fengjun Zhou
Keyword(s):  
Artificial Intelligence ◽  
Numerical Simulation ◽  
Computing Time ◽  
Vertical Direction ◽  
Single Layer ◽  
Oil Production ◽  
Oil Field ◽  
Production Performance ◽  
New Method ◽  
Water Flooding

Abstract The ultimate goal of oilfield development is to maximize the investment benefits. The reservoir performance prediction is directly related to oilfield investment and management. The traditional strategy based on numerical simulation has been widely used with the disadvantages of long run time and much information needed. It is necessary to form a fast and convenient method for the oil production prediction, especially for layered reservoir. A new method is proposed to predict the development indexes of multi-layer reservoirs based on the injection-production data. The new method maintains the objectivity of the data and demonstrates the superiority of the intelligent algorithm. The layered reservoir is regarded as a series of single layer reservoirs on the vertical direction. Considering the starting pressure gradient of non-Newtonian fluid flow and the variation of water content in the oil production index, the injection-production response model for single-layer reservoirs is established. Based on that, a composite model for the multi-layer reservoir is established. For model solution, particle swarm optimization is applied for optimization of the new model. A heterogeneous multi-layer model was established for validation of the new method. The results obtained from the new proposed model are in consistent with the numerical simulation results. It saves a lot of computing time with the incorporation of the artificial intelligence methods. It showed that this technique is valid and effective to predict oil performance in layered reservoir. These examples showed that the application of big data and artificial intelligence method is of great significance, which not only shortens the working time, but also obtains relatively higher accuracy. Based on the objective data of the oil field and the artificial intelligence algorithm, the prediction of oil field development data can be realized. This technique has been used in nearly 100 wells of Bohai oilfields. The results showed in this paper reveals that it is possible to estimate the production performance of the water flooding reservoirs.

Leveraging a New Well Delivery Methodology for Stellar Drilling Results Steam Injection Project Case Study

2021 ◽  
Author(s):  
Carlos Alejandro Terrones Brand ◽  
Miguel Alejandro Basso Mora ◽  
Rajeswary Kandasamy ◽  
Sergio Comarin ◽  
Felipe Rene Bustos Guevara ◽  
...  
Keyword(s):  
Performance Monitoring ◽  
New Technologies ◽  
Service Providers ◽  
Oil Production ◽  
Steam Injection ◽  
Gas Production ◽  
Oil Field ◽  
Superior Performance ◽  
Stringent Performance

Abstract Mexico has set challenging oil and gas production to meet worldwide demand. In order to deliver promised oil production outputs in this challenging environment, the operator came up with efficient partnerships with key service providers to leverage resources and technical know-how whilst encouraging knowledge transfer and drilling project cost reduction. By working with various service companies, the operator creates a competitive environment where each strives to outperform the other. One such success case is in the "S" field, a heavy oil field producing via steam injection in the South of Mexico. Utilizing a creative design and execution methodology, the "S" project team succeeded to deliver improved project performance over the course of drilling the 14 wells in the campaign. The average well operational time was successfully reduced by 10%, hence maximizing the well construction index to 122 m/day and reducing overall well costs. The main strategy to optimize performance is to re-engineer solutions for profitability such as performing a study to replace OBM by WBM, designing a new wellhead system, collaborating with the rig contractor to reduce flat time activities, redesigning cement properties for losses mitigation, improvement of ROP by merging new technologies and local practices, among others. Complementary to this, the strategy is to prioritize realistic areas of improvement by the development and utilization of a new tool called Best of the Best (BoB), a methodology breaking down all well activities in order to measure its fastest time per well and then aiming to achieve that aggressive goal. Detailed follow up in the field allows to reduce operational times by allowing the wellsite team monitor and suggest new and improved ways of doing a routine task all of which result in lower costs per foot. Utilizing this BoB approach and stringent performance monitoring while drilling (pre-actual-post) activity analysis, allowed superior performance to be achieved. The project reached a 60% improvement on well times from the first well drilled to the best performing well. The best well was drilled in 8.68 days versus a field average of 18 days (217 m/day construction index). This generated 369,000 bbls of earlier oil production, 176 days ahead vs client expectations. Furthermore, in coordination with field staff, lessons learned were captured. But this is not enough since fast and effective communication is required, and the BoB methodology provides the solution to share optimization tricks quickly and effectively between crews, to continue well to well improvement and overall project and field level learning. Improved well delivery results is possible only by aligning the detailed planning and execution follow up in both the wellsite and a remote operations centre which monitored drilling activity in real time from town. This synergy and proactive communication system is also a key factor in the project delivery. This paper will present the results from the first application of the ‘Best of Best' (BoB) methodology in Mexico. This successful application enforces the idea that by coupling re-engineering practices to develop a more creative well design along with stringent performance monitoring; any field performance can be improved to deliver stellar results.

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