Dhote, Prashant (Kuwait Oil Company) | Al-Adwani, Talal (Kuwait Oil Company) | Al-Bahar, Mohammad (Kuwait Oil Company) | Al-Otaibi, Ahmad (Kuwait Oil Company) | Chakraborty, Subrata (Schlumberger) | Stojic, Slobodan (Schlumberger)
Subsurface petroleum industry is burdened with uncertainties in every aspect from exploration to production due to limitations of accessibility to reservoir and technology. The most important tools used to understand, quantify and mitigate the uncertainties are geostatistical static modeling and numerical dynamic simulation geomodels. Geomodels are widely used in the industry for characterizing the reservoir and planning favorable development strategy. It is vital instrument for maximizing asset value and optimize project economics.
Static geomodels are foundation for all the advanced numerical and analytical solutions to solve the intricacies of reservoir performance. At the same time, it is where all the static and dynamic geological and engineering observations get integrated to develop common understanding of the reservoir for future studies. Understanding of the above observations and imaging of reservoir framework by individual is the basis for building static geomodels. Hence, at time, the process is highly subjective and proper QC'ing of the models to achieve the general and specific modeling objectives becomes imperative. Simple Questionaries’ based QC'ing and ranking methodologies are also controlled by subjectivity and individual preferences.
In the present endeavor, quantitative ‘Key Performance Indicators (KPIs)’ based standard static geomodeling practices and QC'ing methodologies at corporate level are developed in specially designed "Process Implementation Project (PIP) – Hydrocarbon resource and Uncertainty Management"’ under the aegis of ‘Kuwait Oil Company (KOC) - Reservoir Management Best Practices Steering Committee'.
The main objectives are to establish a practical modeling process, workflows and criteria to standardize modeling processes. A structured self-guidling modeling document has been developed with self-assemment guidelines and questionary. Finally, for each individual process a set of KPIs are specified as minimum standard to meet to obtain the approval of static model.
The present efforts are important for any geologists, geomodelers and reservoir engineers dealing with geostatistical and numerical reservoir modeling and will provide the KPI's based general practices for quality assurance (QA) and QC'ing of the models.
Uncertainty assessment is a crucial step in any 3D geological modeling study, due to the fact that uncertainty exists in all input variables used to build the 3D geological model and due to its subsequent impact on the final in-pace hydrocarbon estimate. Experimental Design (ED) is well-suited to determine the main uncertain parameters, to evaluate the uncertainty impact on production forecasts, and to help accelerate decision making in reservoir development planning. The ED can be used in 3D modeling to minimize the number of model scenarios that are necessary to estimate hydrocarbon in place and predicate reservoir performance profile.
This paper describes in details the major steps of experiment design and propose an optimal procedure to conduct ED study. Topics covered includes how to defining key input variables, the different methods for selecting input distribution shape. Also, this paper covers the dependency between input parameters, ranking methods and results presentation. These concepts are applied on a clastic reservoir to illustrate the benefits of using the ED. Several cases are built using different input data with different distribution shape and dependencies. The results showed that the use of ED captured the potential uncertainty range while reducing the number of models realization needed. The approach is, also, very valuable in assessing the uncertainty of various inputs and their impact on the hydrocarbon in-place volumes.
Nilotpaul, Neog (Kuwait Oil Company) | Narahari, Srinivas Rao (Kuwait Oil Company) | Al-Darmi, Areej (Kuwait Oil Company) | Al-Dousiri Musaed, Yaseen Makki (Kuwait Oil Company) | Rawan, Hussain Al-Mayyas (Kuwait Oil Company) | Tom, De Keyzer (Technically Writes Consultancy) | Peter, Swart (CSL, University of Miami) | Kendall, Christopher G.St.C. (University of south Carolinian)
Field development in complex carbonate evaporite reservoirs has been a challenge for geoscientists by using simple sedimentology based geological models. A high resolution sequence stratigraphic framework has been designed from a conceptual 3D depositional model to a deterministic predictable model. In this process framework boundaries have been fine-tuned with carbon and oxygen isotope signals and defining ichno-facies associations to map lateral continuity of member formations within Marrat sequence. As dolomites and porous grain stones are the key reservoir quality rock types for Marrat Group of formations, position of precursor lithofacies in sequence stratigraphic frame work is found to be crucial. Dolomite samples are analyzed for d13C and d18O. Upper and Lower Marrat members are characterized by thinly laminated, micro crystalline exposure dolomites and high in d18O signal which are associated to low stand packages, whereas Middle Marrat dolomites are relatively low in d18O and high in d13C are associated to high stand precursor facies. Moreover, typical ichnofacies association of porous dolomites defining vertical heterogeneity and lateral connectivity of flow zones in Middle Marrat reservoirs. The reliability of this model has been established through recent tested intervals, with production logging and formation pressure tester data integration demonstrates predictability of flow zone connectivity.