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Quantifying the uncertainty in the ultimate recoverable oil reserves using the Monte Carlo simulation techniques from ‘OWA’ Marginal Field, Onshore Niger Delta, Nigeria

Adeigbe O. C., Odedere I. F., Amodu O. I.

Geology, Geophysics and Environment

2018

Vol. 44, no. 4

401--412

A review on the development of marginal oil fields in Nigeria has now become an important strategic issue if it is to remain amongst the top producers in the global market, and these fields are vast, available all over the Niger Delta. One of the factors that makes a field marginal is the size of its reserves. Stochastic estimation gives a certainty in terms of the possible number of outcomes within the range of input parameters. In this work, four (4) deviated wells and 3D seismic volume (362 inlines and 401 traces) were interpreted for the evaluation of the field. The petrophysical evaluations were interpreted using the Power Log software and the Seismic, Geographix and Petrel softwares. Stochastic reserve estimation was done using Monte Carlo sampling techniques and subjected to uncertainty quantification using the Crystal Ball software by varying distributions and measuring sensitivity impact on the overall reserves. The production profile was predicted based on some assumptions and history matching which result in the overall Expected Ultimate Recovery (EUR). The petrophysical analysis shows the reservoirs to be within the unconsolidated continental Benin Formation denoted as ‘Intra-Benin’ sands, an unconventional reservoir as supposed the normal reservoir rocks within the Agbada Formation. This indicated high porosity (0.28), water resistivity (7 Ω∙m), and water saturation and also inferred Heavy Oil (low API). Nine hydrocarbon sands were identified but only three (B1, D and E), representing shallow, mid and deep reservoirs were further evaluated. 1P and 2P reserve estimates were 4.8 MMBO and 5.7 MMBO for B1; 15.2 MMMscf and 16.4 MMMscf for D; 8.4 MMMscf and 8.8 MMMscf for E respectively. The Monte Carlo simulation of 1,000,000 trials with mainly triangular distribution assumption generated P10, P50, P90 were 6.5 MMBO, 5.6 MMBO and 4.4 MMBO for B1; 17.5 MMMscf, 13.7 MMMscf and 10.8 MMMscf for D; 10.4 MMMscf, 8 MMMscf and 6.1 MMMscf for E respectively. The sensitivity impact of the input parameters were estimated and ranked, and the coefficient of variability ranges within 15% to 20% for the reservoirs indicating that there is a very low level uncertainty of reserve estimation around the P10, P50 and P90 percentiles which could be positive for investment decisions. ‘OWA’ marginal field reflects a typical low reserve (EUR) category found within the Niger Delta basin.

Miasta Rzymu

Janowski M

Zeszyty Naukowe Politechniki Poznańskiej. Architektura i Urbanistyka

2012

Z. 27

21--31

Artykuł jest próbą spojrzenia na Rzym jako na realizację kolejnych założeń urbanistycznych, będących odwołaniami do ideałów, które były nieustannie zmieniane i konfrontowane z chaotyczną zabudową. Przedstawiono w nim próby wprowadzenia porządku za pomocą wyrazistych zespołów budynków. Jest też próbą znalezienia elementów wspólnych - materialnych i niematerialnych - łączących kolejne „miasta", które współtworzą Rzym.

The article is an attempt to look at Rome as the subsequent implementation of urban planning to apppeal to the ideals that were constantly changed and confronted with the chaotic architecture. It shows the attempts to introduce order by distinct groups of buildings. There is also an attempt to find common elements - material and intangible -that provides more "city" who contribute to Rome.