The traditional way of acquiring reservoir fluid samples (prior to production) has usually involved running a wireline formation tester for several days or even weeks after drilling the well. This time delay between drilling and sampling has an adverse effect on obtaining high quality fluid samples because of long-term exposure to invasion. This effect becomes worse in low permeability formations where effective mud-cake build-up is poor, resulting in deeply invaded formations. In turn, this requires large volumes of filtrate to be pumped back out of the formation in order to collect low contamination reservoir fluid samples. The ability to sample while drilling using LWD technology solves part of this problem by allowing the pump-out to start much earlier in the invasion process, thereby reducing the volume of filtrate required to pump out of the formation. In addition to cost-savings from reduced sampling time, there are other benefits to LWD sampling such as continuous circulation. This can be critical when multiple reservoirs are exposed, some of which may be depleted and pose differential sticking risks, which is often the case in the Middle East. However, current LWD sampling technology is done with a probe which limits the inflow area thereby complicating the sampling process in low permeability formations. Many of the giant carbonate reservoirs in the Middle East are highly heterogeneous and have low average permeabilities (<1-5mD) making it difficult to sample with a standard probe in many situations (LWD technology cannot overcome all the challenges just yet). But viscosity is also critical and the overall mobility of gas reservoirs can be relatively high due to the low gas viscosity, thereby making gas samples a potential application for this new LWD technology in Middle East carbonate reservoirs. Formation pressures and fluid samples were taken from such a reservoir. In this field there is known condensate banking and the project involves re-injecting the produced dry gas into the reservoir to help maximize the condensate recovery. Seven (7) samples were collected using an LWD sampling tool, and subsequent lab analysis on the samples confirmed condensate in the reservoir. This new technology is seen as a way to help maximize recovery and minimize costs.

This paper presents the development of a tightly-coupled Integrated Asset Model (IAM) to capture the surface-subsurface interactions of 5 gas condensate reservoirs producing through a common surface facilities network. The objective of the exercise is to develop a tool that is built to combine existing compositional simulation models and the surface network model in a single platform/environment that could be used in production optimization, de-bottlenecking, field development and flow assurance. The success criteria included providing a solution that can ensure: Adequate representation of the different fluids of the 5 reservoisFull adherence to existing network constraints and field development guidelinesProviding optimal network configuration based on the use of automatic production optimization procedures.Flexibility to add complex network elements and decision logic The most powerful and unique feature that enabled all of the above was the effective use of procedures and built-in functions in Nexus that offer the capability to incorporate operational considerations into the solution. The first step involved developing a common fluid components basis to be used for the surface and subsurface models. This was achieved through adopting a suitable lumping scheme that involved minimal adjustment to the existing equations of state (EOS) and no compromise of the fluid description or the quality of the history matches Next step involved converting all the five reservoir models and their surface network model into the same simulation environment. The final step involved developing the procedures that carried out production optimization and proposed the optimal settings to fully utilize the available compression capacity. Finally, the surface elements of the IAM were calibrated to the results of production capacity tests. The calibration involved matching the observed gas production rates, tubing head pressures and flowline pressures. This step is required to validate the constrained model performance and prediction. The results showed the magnitude of interaction between the reservoirs and clearly identified the system bottlenecks. The model can be used to propose the best tie-in location of future wells in addition to providing first-pass flow assurance indications by highlighting elements of the network at risk of erosion throughout the field's life and under different network configurations.

A giant lean gas reservoir overlying a large oil rim is producing for more than 27 years became under depletion mode without any pressure maintenance. Formation collapse in reservoirs under depletion can cause permeability reduction, completion damage and well failure, reducing or even interrupting production and affecting the ultimate recovery from the reservoir. It is therefore critical to predict any risk in formation collapse. If such risks exist, recommendations are required to optimize reservoir management. Stress measurements were acquired and core analysis were performed in intact rocks area and used for 1D MEM (Mechanical Earth Model) and 3D MEM. 1D MEMs for 10 wells were constructed. Rock mechanical tests were conducted on core samples. 3D MEM was created with 13 interpreted seismic overburden horizons and 105 seismic faults. Four scenarios were performed to identify formation failure during the scheduled production. The worst-case scenario will happen of reservoir depletion, in case of weak formation and reactivated faults. Intensive logging, fracture modelling, coring program across the main fault corridor and RMT (Rock Mechanics Tests) were performed in vertical and horizontal holes across the fault corridor area to fulfil gaps of rock mechanical properties (elastic properties and rock strength) and field stresses. The acquired data were seeds for Lab testing, fracture network analysis and fault characterization which used to update the 3D MEM. Additional Lab tests to fill gaps in rock samples with high porosity (> 30%) were carried out and 1D MEM of 5 more wells were constructed, and the 3D MEM were updated. The 2017 updated 3D MEM eliminates three of the 2013 four scenarios and ended up with one robust scenario that shows better reservoir integrity and very small localized areas of pore collapse in high porosity regions only (> 30%) compare to the previous model. The reservoir can produce under depletion mode with production optimization in areas of expected compaction. Well integrity study and compaction monitoring are also considered to be commentary studies.

TX 75083-3836, U.S.A., fax 01-972-952-9435. SummaryThis paper gives a Field case history of a giant multilayer carbonate reservoir located offshore Abu Dhabi. This reservoir has field-wide lower permeability Stylolite layers between the main producing zones. Interestingly, some water hold up phenomena has been observed above Stylolite layers which gives doubt on the degree of vertical communication between the different reservoir producing zones (Fig. 1). This phenomenon can be related to the negative capillary forces in the oil wet reservoir rock and/or the vertical permeability across the Stylolite layers.An integrated approach is given for the evaluation of water hold up by investigating both the vertical transmissibility across the Stylolite layers throughout the reservoir and the capillary forces due to oil wetting characteristics of the carbonate rock. The results of different methods for evaluation of the vertical permeability (Kv) will be given. These methods include: laboratory results from whole core vertical permeability (Kv) measurements at reservoir conditions using brine, multi-well vertical interference tests (VIT), single well VIT across the stylolite layers combined with MDT/RFT data, specially designed tracer injection tests in dual injector/producer well, and estimations from transient well test data for horizontal wells. Laboratory measurements of capillary pressure at reservoir conditions will also be shown explaining its role in water hold up.The results from a simulation sector model study will be presented for assessment of vertical communication through Stylolite layers by integrating different sources of data. This study quantifies the effect of Kv uncertainty on the expected field performance.

Natural fractures can have a significant impact on fluid flow by creating permeability anisotropy in hydrocarbon reservoirs. They can also play an undesirable role on reservoir subsidence and compaction during depletion, with important consequences for production strategy and well and surface facility equipment. The investigation of these possible fracture effects motivated a comprehensive integrated fracture study of three reservoirs from a giant gas-condensate field in Abu Dhabi. The main objective of the study was to build representative 3D fracture models and compute fracture properties of each reservoir, to be used in future accurate dynamic simulations. The results of the fracture study were also used to define the risk associated with the geomechanical integrity of the reservoirs. The integrated workflow included several approaches, all contributing towards the global understanding of the fracture distribution and flow impact in the reservoirs. The static fracture characterization involved detailed seismic inversion and fracture characterization, core and borehole image analysis. It focused on the identification of the fracture components occurring in the reservoirs and their geometrical properties and spatial distribution. This was complemented by a study of the well dynamic data (e.g. fluid injection/production data, well tests, flowmeters, static pressure data), carried out to evaluate the dynamic impact of the fractures by identifying wells showing anomalous dynamic behaviors. The integration of static and dynamic data allowed the identification and quantification of which fracture components played a role on fluid flow in the reservoirs. The results of the static and dynamic data analysis were integrated to develop a 3D Discrete Fracture Network (DFN) model of each reservoir, reflecting the fracture organization identified during the characterization stage. The hydraulic properties of fractures (aperture and conductivity) were determined using flowmeter and well test data. The calibrated fracture models were then upscaled as to compute equivalent fracture properties (fracture porosity, permeability tensor and equivalent matrix block sizes or shape factors) to be used in further full-field reservoir simulation models. The results of the study concluded that the reservoirs are dominated by the presence of large scale fracture corridors that were modelled deterministically in the DFNs based on the integration of well and seismic data. There is also a negligible, unconnected small scale diffuse fracturing in the reservoirs, with no flow impact. The fluid production is mainly controlled by matrix support with very limited contribution from fracture corridors. Finally, the very limited fracturing detected suggests no major risk in terms of reservoir integrity. The integrated study carried out allowed the development of accurate, consistent fracture models for the three studied reservoirs. The uncertainty associated with the fractures and their impact was properly addressed, allowing building better field development plans and defining risk-free reservoir depletion strategies.