Though there are various methods to assess reservoir performance, historical methods seem to focus the assessment on a single or couple of parameters. These include traditional methods to evaluate the reservoir sweep through average oil saturation-thickness maps, remaining oil volume maps, etc. Optimum reservoir management is a challenging and time consuming process since it usually involves analyzing many reservoir properties such as porosity, permeability, thickness, hydrocarbon saturation, fluid properties, relative permeability, net-to-gross ratio and pressures. In this work, we incorporate all these parameters into an automated workflow for reservoir diagnostics; and identification and ranking of optimum hydrocarbon (HC) targets.
The proposed workflow extracts static and dynamic information from reservoir simulation outputs and performs additional post-processing calculations on each grid cell for all time steps. The methodology involves classification of the reservoir simulation grid cells based on fluid saturation, relative permeability, pressure changes and displacing phase fluxes. After that, Produced, Mobile and Immobile oil volumes are calculated for each cell. These volumes are then grouped into six categories, namely, Produced, Highly Contacted, Moderately Contacted, Minimally Contacted, Uncontacted and Immobile Oil. In addition, the workflow incorporates different indicators for determining grid cell quality. These indicators are Reservoir Opportunity Index (ROI) and Simulation Opportunity Index (SOI); and we proposed a new reservoir quality indicator that incorporate changes in pressure over time. Finally, the workflow identifies connected cells with high quality indices and ranks these regions based on size and/or grid cell quality as potential targets for infill drilling.
The presented automated workflow is introduced as an integral part of well placement optimization workflow. It has been tested on several simulation models and successfully identified and ranked un-swept reservoir regions which proved through dynamic simulations to be credible future drilling targets.
Raudhatain field located in North Kuwait produces hydrocarbons from over 230 wells into Gathering Center X with varying complex geometries, completions and downhole equipment. NK asset team is executing a project of modeling the entire NK production system starting with wells in Raudhatain field producing to GC-X, involving building models for the wells and the gathering surface network of flow lines.
There are numerous challenges that the NK asset team is facing in meeting production targets, including controlling water/gas breakthrough in horizontal wells. Mitigation measures include installation of inflow control devices (ICDs). Since inception a decade ago this proven technology has long been used in many oilfields around the world and is increasingly being installed in horizontal wells in Kuwait. To date there are several horizontal wells in Raudhatain field completed with ICDs.
Reservoir modeling and simulation approach is frequently used in the industry capturing the behavior of existing ICD wells. This approach uses conventional modeling tools that are typically more intricate and require expert skills in capturing the dynamic behavior of the wellbore and the reservoir which is less appealing to the operations and practicing engineers.
Limited with time and resources in this project, the NK team took a relatively simpler and fast approach in modeling existing ICD wells in Raudhatain field with the aim of enabling the engineers to capture the behaviour of the wells using existing production engineering tools at their disposal.
The approach can be summarized as follows: Establishing the well performance Modeling the individual ICD sections in accordance to the approximate flow distribution/geometry along the horizontal well Matching the well with well test data
Establishing the well performance
Modeling the individual ICD sections in accordance to the approximate flow distribution/geometry along the horizontal well
Matching the well with well test data
Key benefits of this approach are: Enabling the engineers to quickly model the ICD wells. Facilitated the use of existing tools to deliver engineering models fit for use in the production system. Serves the purpose of high level modeling of complex ICD wells and in the future this exercise will certainly be undertaken to capture wellbore hydraulic effects. ICD well models are timely added into the gathering network which would otherwise have been delayed using a conventional method.
Enabling the engineers to quickly model the ICD wells.
Facilitated the use of existing tools to deliver engineering models fit for use in the production system.
Serves the purpose of high level modeling of complex ICD wells and in the future this exercise will certainly be undertaken to capture wellbore hydraulic effects.
ICD well models are timely added into the gathering network which would otherwise have been delayed using a conventional method.
Jamal, Mariam (Kuwait Oil Company) | Anthony, Elred (Kuwait Oil Company) | Chetri, Hom B (Kuwait Oil Company) | EL-Din Ibrahim, Hossam (Kuwait Oil Company) | Kumar, Priya ranjan (Kuwait Oil Company) | Nair, Sajan (Kuwait Oil Company) | Al-Zaabi, Hamad (Kuwait Oil Company)
Within a natural fractured Carbonate Reservoir a NOC's Overall production rates are constantly challenged with factors, such as high permeability streaks, poor macroscopic sweep efficiency, and low mobility ratios, all of which can dramatically impair production rates and reservoir oil recoveries.
The need to develop new tools that allow reservoir engineers to optimize reservoir performance is becoming more demanding by the day. One of the most challenging and influential problems facing reservoir engineers is well placement optimization.
The North Kuwait field (NKF) consists of six fields containing four naturally fractured carbonate formations. The reservoirs are composed of relatively tight limestone and dolomite embedded with anhydrate and shale. The fields are divided into isolated compartments based on fault zones and supported by a combination of different fluid compositions, initial pressures, and estimated free-water levels. Due to natural complexity, tightness, and high drilling costs of wells in the NKF, it is very important to identify the sweet spots and the optimum well locations.
This paper presents two intelligent methods that use dynamic numerical simulation model results and static reservoir properties to identify zones with a high-production potential: reservoir opportunity index (ROI) and simulation opportunity index (SOI). The Petrel* E&P software platform was chosen as the integrated platform to implement the workflow. The fit-for-purpose time dependent 2D maps generated by the Petrel platform facilitated the decision-making process used for locating new wells in the dominant flow system and provided immense support for field-development plans.
The difference between the two methods is insignificant because of reservoir tightness, limited interference, and natural uncertainty on compartmentalization. At this stage, pressure is not a key parameter. As a result, unlike brown fields, less weight was given to simulated pressure, and SOI was used to select the well locations.
The results of this study show that implementing these workflows and obtaining the resulting maps significantly improve the selection process to identify the most productive areas and layers in a field. Also, the optimum numbers of wells using this method obtained in less time and with fewer resources are compared with results using traditional industry approaches.
North Kuwait had discovered several deep reservoirs during 1960s which were not considered for development production till 2010 because of higher priority given to the major reservoirs such as Mauddud and Burgan. Zubair and Ratawi are two such new reservoirs, taken up for fast track development since last 2 years.
In order to achieve the production target for the asset, ZU/RT need to be brought to production. A complete evaluation of all geological/ Geophysical data was done for all penetration through ZU/RT. All testing results available during the exploratory wells were comprehensively gathered and evaluated. Based on the data, fast track well release, drilling & completion were initiated. The objective was to gain production as well as data to reduce the uncertainty for further development and reservoir modeling work. The initial results indicated tremendous challenges in terms of fluid regime as well as reservoir rock properties.
The production, at the beginning of the project, was zero, which has now been increased to about 20 MBOPD within a year. Integrated team work and calculated risks helped to achieve this milestone.
The paper aims to share the challenges and the lessons learnt during the production delivery from the new reservoirs in North Kuwait.
Geological Background/ Setting
Sabiriyah Zubair is a minor reservoir of clastic type, which was on low priority for development/ production since discovered druing 60s.. This is a relatively small reservoir in terms of size and potential, as compared to other major reservoirs in Sabiriyah field viz. Mauddud & Burgans. However, the accomplished intial tests at two wells (SA-00271 and SA-0278) indicate that the reservoir has mobile oil and can participate to contribute to NK overall production. Currently 7 wells are flowing to Gathering centre at total rate of about 10 MBOPD.