Using Different Methods to Predict Oil in Place in Mishrif Formation / Amara Oil Field


  • Mohammad Najeeb University of Technology, Petroleum Technology Department, Iraq
  • Fadhil Sarhan Kadhim University of Technology, Petroleum Technology Department, Iraq
  • Ghazwan Noori Saed University of Kufa, Chemical Engineering Department, Iraq



OOIP, reserve estimation, Monte Carlo Simulation, HIIP


The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of reserve estimation used for the Mishrif formation / Amara oil field volumetric approach in mathematic formula (deterministic side) and Monte Carlo Simulation technique (probabilistic side), material balance equation identified by MBAL software and reservoir simulation adopted by  Petrel software geological model.  The results from these three methods were applied by the volumetric method in the deterministic side equal to (2.25 MMMSTB) and probabilistic side equal to (1.24, 2.22, 3.55) MMMSTB P90, P50, P10 respectively. OOIP was determined by MBAL software equal to (2.82 MMMSTB). Finally, the volume calculation of OOIP by using the petrel static model was (1.92 MMMSTB). The percentage error between material balance and the volumetric equation was equal to 20% while the percentage error between the volumetric method and petrel software was 17%.


Igbokwe and L. Chidozie, "Comparative analysis of reserve estimation using volumetric method and Mbal on Niger Delta oil fields", University of Technology of Owerri, published Thesis, Nigeria, 2011.

Maksim Y. Nazarenko, "Probabilistic production forecasting and reserves estimation in water flooded oil reservoirs", Texas A&M University, published Thesis, USA. 2016.

Robert Kosova, Adrian Naco and Irakli Prifti, "Deterministic and Stochastic methods of oil field reserves estimation: A case study from KA. Oil field", Interdisplinary Journal of Research and Development, Vol. (IV), No.2, 2017, pp226-231.

Petroleum Resources Management System (PRMS) , Society of Petroleum Engineers (SPE), American Association of Petroleum Geologists (AAPG), World Petroleum Council (WPC), Society of Petroleum Evaluation Engineers (SPEE), Society of Exploration Geophysicists (SEG), Society of Petro physicists and Well Log Analysts (SPWLA), European Association of Geoscientists & Engineers (EAGE). 2017.

Kosova Robert, Shehu Valentina, Naço Adrian, Xhafaj Evgjeni, Stana Alma, Ymeri Agim, "Monte Carlo Simulation For Estimating Geologic oil Reserves. A Case Study Kuçova Oil Field In Albania" 2015, pp. 20-25

P.F. Worthington, "Reserves—Getting It Right", International Petroleum Technology Conference, IPTC 10809, Doha, Qatar. 2005.

Hugo Araujo and Aquiles Rattia, "Reserves Follow-up Using an Integrated Deterministic-Probabilistic Approach", SPE 143843, Colorado, USA. 2011.

Buraq Adnan Al-Baldawi, "Applying the cluster analysis technique in logfacies determination for Mishrif Formation, Amara oil field, South Eastern Iraq" , Arabian Journal of Geosciences, Volume 8, Issue 6, 2014, pp3767-3776.

Jawad K. Radhy AlBahadily and Medhat E. Nasser, "Petrophysical Properties and Reservoir Modeling of Mishrif Formation at Amara Oil Field, Southeast Iraq", Iraqi Journal of Science, Vol. 58, No.3A, 2017, pp1262-1272.




How to Cite

Najeeb, M., Kadhim, F. S., & Saed, G. N. (2020). Using Different Methods to Predict Oil in Place in Mishrif Formation / Amara Oil Field. Iraqi Journal of Chemical and Petroleum Engineering, 21(1), 33–38.