Science Explorer Interactive view Map

Reservoir Engineering and Simulation Methods

Reservoir Engineering and Simulation Methods is a research topic within Ocean Engineering. Science Explorer counts 61k research works in it since 1950. 11.2% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on advanced techniques in reservoir management, including the use of Ensemble Kalman Filter for data assimilation and model updating, optimization of well placement and production operations, uncertainty quantification in production forecasting, and closed-loop control strategies. The research also covers topics such as smart wells, history matching, and the integration of geological models for improved reservoir characterization.

  • Ensemble Kalman Filter
  • Optimization
  • Data Assimilation
  • Well Placement
  • Uncertainty Quantification
  • Closed-Loop Control
  • Smart Wells
  • History Matching
  • Production Forecasting
  • Geological Models
Research works
61k
fractional, since 1950
In the world top 10%
6.8k
per year above
Top-10% rate
11.2%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+19%
the tick is no change

Which countries lead Reservoir Engineering and Simulation Methods research?

By volume, China and the United States publish the most (2.3k and 1.7k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2.3k works
  2. 2 United States 1.7k works
  3. 3 Russia 451 works
  4. 4 United Kingdom 385 works
  5. 5 Brazil 333 works
  6. 6 India 292 works
  7. 7 Indonesia 274 works
  8. 8 Nigeria 252 works
  9. 9 Malaysia 251 works
  10. 10 United Arab Emirates 241 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 35.7%United States: 25.8%Russia: 7.0%United Kingdom: 6.0%6 others listed: 25.5%36%largest
China2,307 · 35.7%United States1,668 · 25.8%Russia451 · 7.0%United Kingdom385 · 6.0%6 others listed1,644 · 25.5%

Shares of the rows listed above, not of the whole node.

Which institutions lead Reservoir Engineering and Simulation Methods research?

By volume in 2022–2025, Research Institute of Petroleum Exploration and Development publishes the most Reservoir Engineering and Simulation Methods research, followed by China University of Petroleum, Beijing and Abu Dhabi National Oil (United Arab Emirates).

Where is Reservoir Engineering and Simulation Methods research done?

The largest centres of Reservoir Engineering and Simulation Methods research in 2022–2025 are Beijing (China), Houston (United States), Abu Dhabi (United Arab Emirates) and Daqing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Road Town, Arbroath and San Ramon.

Largest cities, 2022–2025

  1. 1 Beijing China 959 works
  2. 2 Houston United States 301 works
  3. 3 Abu Dhabi United Arab Emirates 220 works
  4. 4 Daqing China 202 works
  5. 5 Chengdu China 192 works
  6. 6 Kuala Lumpur Malaysia 178 works
  7. 7 Qingdao China 156 works
  8. 8 Moscow Russia 147 works
  9. 9 Rio de Janeiro Brazil 147 works
  10. 10 Dhahran Saudi Arabia 144 works

Where it is the local speciality

  1. Road TownVG · 90.3 works309×
  2. ArbroathGB · 72.7 works290×
  3. San RamonUS · 27.6 works107×
← less than its size predictsmore →

Location quotient: how much more of its research is in Reservoir Engineering and Simulation Methods than the world average.

See Reservoir Engineering and Simulation Methods on the map

Where is the best place to study Reservoir Engineering and Simulation Methods?

Among universities, judged by research, King Abdullah University of Science and Technology, Saint Petersburg Mining University and Amirkabir University of Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 19.11%fractional works in this node (log) →share in the world top 10% →King Abdullah University of Science and Technology: 39, 20.5%Saint Petersburg Mining University: 17, 37.7%Amirkabir University of Technology: 24, 29.8%King Fahd University of Petroleum and Minerals: 54, 12.7%University of Tulsa: 24, 25.7%China University of Petroleum, Beijing: 200, 13.6%China University of Petroleum, East China: 121, 13.3%Universiti Teknologi Petronas: 23, 12.6%Ufa State Petroleum Technological University: 52, 7.1%University of Houston: 25, 18.1%Saint Petersburg Min…Amirkabir University…King Abdullah Univer…King Fahd University…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 King Abdullah University of Science and TechnologySaudi Arabia 67.320.5%14.6×39 +100.7%
2 Saint Petersburg Mining UniversityRussia 66.137.7%31.1×17
3 Amirkabir University of TechnologyIran 64.729.8%10.0×24 +63.4%
4 King Fahd University of Petroleum and MineralsSaudi Arabia 62.412.7%16.3×54 +122.2%
5 University of TulsaUnited States 59.325.7%44.3×24 +38.4%
6 China University of Petroleum, BeijingChina 57.813.6%53.7×200 -28.5%
7 China University of Petroleum, East ChinaChina 57.513.3%26.7×121 +22.9%
8 Universiti Teknologi PetronasMalaysia 57.212.6%15.7×23 +110.8%
9 Ufa State Petroleum Technological UniversityRussia 57.17.1%79.0×52 +1729.5%
10 University of HoustonUnited States 54.918.1%7.9×25 +131.9%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Reservoir Engineering and Simulation Methods research growing?

Output in 2018–2022 was 19% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Reservoir Engineering and Simulation Methods.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.