Glover, Paul W. J. (University of Leeds) | Lorinczi, Piroska (University of Leeds) | Al-Zainaldin, Saud (University of Leeds) | Al-Ramadhan, Hassan (University of Leeds) | Sinan, Saddam (University of Leeds) | Daniel, George (University of Leeds)
New reservoirs are increasingly more heterogeneous and more anisotropic. Unfortunately, conventional reservoir modelling has a resolution of only about 50 m, which means it cannot be used to model heterogeneous and anisotropic reservoirs effectively when such reservoirs exhibit significant inter-well variability at scales less than 50 m. This paper describes a new fractal approach to the modelling and simulation of heterogeneous and anisotropic reservoirs. This approach includes data at all scales such that it can represent the heterogeneity of the reservoir correctly at each scale.
Three-dimensional Advanced Fractal Reservoir Models (AFRMs) can be generated easily with the appropriate code. This paper will show: (i) how 3D AFRMs can be generated and normalised to represent key petrophysical parameters, (ii) how these models can be used to calculate permeability, synthetic poro-perm cross-plots, water saturation maps and relative permeability curves, (iii) the effect of altering controlled heterogeneity and anisotropy of generic models on fluid production parameters, and (iv) how AFRMs which have been conditioned to represent real reservoirs provide a much better simulated production parameters than the current best technology.
Results of generic modelling and simulation with AFRMs show how total hydrocarbon production, hydrocarbon production rate, water cut and the time to water breakthrough all depend strongly both on heterogeneity and anisotropy. The results also show that in heterogeneous reservoirs, the best production data is obtained from placing both injectors and producers in the most permeable areas of the reservoir – a result which is at variance with common practice. Modelling with different degrees and directions of anisotropy shows how critical hydrocarbon production data depends on the direction of the anisotropy, and how that changes over the lifetime of the reservoir.
We have developed a method of fractal interpolation to condition AFRMs to real reservoirs across a wide scale range. Comparison of the hydrocarbon production characteristics of such an approach to a conventional krigging shows a remarkable improvement in the modelling of hydrocarbon production when AFRMs are used; with AFRMs in moderate and high heterogeneity reservoirs returning values always within 5% of the reference case, while the conventional approach often resulted in systematic underestimations of production rate by over 70%.
Random seismic noise, present in every authentic seismic data set, hampers both geoscientists’ manual interpretation of data and computerized delineation and analysis of seismic features. Therefore, many noise suppression techniques have the goal of preserving image quality. For channel detection, accurately suppressing seismic noise without damaging image detail is crucial. Theoretically, channel patterns can be automatically detected owing to their unique spatial footprint, which differentiates them from other three-dimensional seismic features. One notable characteristic of channels is their local linearity: Their spatial extent is much greater in one direction than in any other direction. A variety of techniques, such as spatial filters, can enhance the “slender” characteristic of channels. Unfortunately, most of these techniques reduce noise by smoothing the data, resulting in a loss of edge definition. During the past few years the literature has revealed several new edge-preserving noise reduction techniques, including edge-preserving smoothing and complex wavelet transforms. In this case study I illustrate the performance of edge-preserving smoothing based on the redundant wavelet transform (RWT) and demonstrate its usefulness before running an edge detection algorithm to reveal channel patterns in seismic data from Saudi Arabia. Our examples demonstrate that RWT can successfully preserve, enhance, and delineate channel edges that are otherwise not readily visible on conventional seismic amplitude displays.
Channel detection is an important part of seismic interpretation for oil and gas exploration. In theory, channel patterns should be possible to detect automatically owing to their unique spatial footprints, which differentiate them from other features encountered in 3D seismic data. One notable characteristic of channels is their local linearity; that is, their extent is much greater in one direction than in any other direction. Traces of a channel can typically be seen on a seismic time slice.
Spatial filters are commonly used to remove noise from seismic data. Unfortunately, most smooth the data to reduce noise (Jervis 2006). During the past few years researchers have developed several new 3D seismic noise reduction techniques that preserve edges, including edge-preserving smoothing (Blumentritt et al. 2003) and complex wavelet transforms (Jervis 2006).
Here I use the same mechanism Al-Dossary and Ananos (2012) used to demonstrate the effects of applying the redundant wavelet transform (RWT) (Shensa 1992) before edge detection and subsequent channel identification.
Al-Dossary and Ananos (2012) demonstrated the usefulness of RWT before edge detection to enhance channel patterns in seismic data. In this paper I apply the concept to data collected from Saudi Arabia. The RWT is a type of discrete wavelet transform (DWT). However, it differs from the standard DWTs in that it does not carry out decimation or subsampling at successive resolution levels; rather, RWT decomposes the data into low-frequency information (approximation) and high-frequency information (wavelet coefficients) to obtain a projective decomposition of the data into different scales. RWT can be used for noise reduction in image processing, texture classification, and image fusion. RWT’s advantage in feature characterization lies in its pixel-wise analysis of images without performing image decimation. After application of RWT, locally linear features appear at adjacent scale levels, whereas non-significant features such as random noise slowly decrease as the scale level increases. I demonstrate RWT’s effectiveness by applying it to seismic data over a channel from Saudi Arabia. The input data are a time slice extracted from the Hawtah field in central Saudi Arabia.
With the world’s increasing energy demand, it has become more crucial to safely and efficiently maximize recovery from existing assets. In this effort, there are compelling reasons for focusing on clastic reservoirs where horizontal wells are drilled to maximize reservoir contact and drainage area. In this environment, well placement and real-time petrophysical evaluation are the keys to maximizing net-to-gross ratios.
Technology has recently evolved toward the adaptation of a multi-disciplinary approach and integration of real-time answer products to address formation evaluation challenges. To this end, Saudi Aramco has introduced into their lateral operations the slim size LWD spectral gamma ray in combination with the multi-functional logging while drilling (LWD) technology.
By measuring a formation’s three naturally occurring radioactive components: potassium (K), uranium (U), and thorium (Th) in real-time, petrophysicists can identify clay mineral types in addition to the standard evaluation. This information allows for more accurate formation evaluation through reliable optimizing petrophysical modeling of mineral and fluid types and volumes. It also minimizes uncertainty on the volume of shale (Vsh) estimation, which has an impact on the effective porosity calculations.
From real-time 16-bin spectral gamma ray data and X-Y magnetometers to track the detectors azimuthal position, a high resolution image is preferred — over the standard gamma ray — for properly identifying target entry and for optimizing well trajectory in clastic formations where the lithology changes vertically and laterally.
Technology Description and Application:The Slim LWD Spectral Gamma Ray tool measures total gamma ray of a formation and the three previously noted naturally occurring radioactive components (K, U, Th). This technology is used in slim holes as well as in relatively larger holes with the 6.75” or 4.75” collar sizes. To produce a real-time azimuthal gamma ray image, the tool must be rotated and run with “s” directional sensors. The 6.75” tool has three (3) spectral detectors and the 4.75” with one (1) detector. Each scintillation-based detector is mounted in a pocket on the outside of the collar with a thin protective sleeve over the detectors; thus enabling the highest possible gamma energy to reach the detectors.
Forsyth, D. (Saudi Aramco) | Witjaksono, M. (Saudi Aramco) | Palmer, R. (Saudi Aramco) | Silva, A. (Saudi Aramco) | Najrani, Hussain (Saudi Aramco) | Zeghlache, Mohamed L. (Saudi Aramco) | Mitchell, P. (ETS Laboratories)
The main Permian Reservoirs in Central Saudi Arabia have presented an evaluation challenge because of the presence of fresh-brackish water encountered directly below the hydrocarbon accumulations. If this water is used in the evaluation of the oil zone then high connate water saturation is obtained which is inconsistent with generally initial water free oil production observed in the field. Early field development evaluation pragmatism assumed a dual salinity model. Higher salinity formation water was used for the evaluation of the oil zone and fresher water used for evaluation of the underlying water zone. The oil zone formation water was assumed to be the original depositional water present at the time of oil migration. High salinity can be typical for an Arid Fluvial–Estuarine system with high evaporation. Oil migration trapped this water in place. Post-hydrocarbon migration, Paleozoic rain water from higher elevations of the Arabian Shield recharged and flushed the original water beneath the oil. Practical issues have limited confirmation of this assumption and no measurements have been taken to confirm the oil zone water salinity or the dual salinity model.
A new technique is being explored that involves extraction and analysis of small quantities of fluid from core plugs sampled at the rig site. Invasion is quantified using mud doping. Initial results show that there is indeed evidence for higher salinity water present in the hydrocarbon zone compared with fresher water in the aquifer, consistent with the proposed dual salinity model. Extended testing of the technique has been conducted which shows that it can be used to measure water salinities in even very tight rock (~micro Darcy). The potential of the technique is to provide a more reliable fluid discriminator, both in these low relief difficult to evaluate formations, and in exploration and unconventional areas.
The pre-Khuff principal hydrocarbon reservoir, Unayzah Formation, consists mainly of distal braid plain sandstones characterized by aeolian and sabkha facies with minor fluvial units. It extends between the pre-Khuff and the Hercynian unconformities. In Abu Dhabi, the Unayzah-A is further subdivided into three members, Members 1 and 2 are comprised of sandstone reservoirs and Member 3 consists of siltstone and shale sediments.
Facies controls on reservoir quality are weak. The main controls on porosity reduction of the reservoir are mechanical compaction and silica cementation. Quartz cementation tends to be the most severe in the cleanest, coarsest sandstones and near certain fractures. The presence of clay mineral grain coatings, although reducing the permeability, but locally protects the rock from secondary quartz overgrowth and preserve the porosity to great depths of burial. Without the grain coating, porosity will decrease with depth until the reservoir rock is completely tight.
Unayzah reservoir seals are provided by the Basal Khuff Clastics, tight Basal Khuff Carbonate and Middle Khuff Anhydrite. The Basal Khuff Carbonate seal does not appear to be regionally extensive but localized and potentially prospect specific. However, there are insufficient data to accurately define the seal for the Unayzah hydrocarbon accumulations.
Due to lack of deep penetrations in Abu Dhabi, basin modeling for Silurian hot shale source rock is challenging. Therefore, much of the unknown source and tectonic information were derived from the surrounding countries. This comes from understanding the regional tectonics and depositional trends of the southeastern Arabian plate, which helped to extrapolate the source trends into the Abu Dhabi area. The basin model shows that oil from Silurian source rock was generated early in the basin history and was widespread by the Late Triassic (220 Ma). Significant gas generation occurred during Lower Cretaceous (140 Ma) and dominated the hydrocarbon system by Middle Cretaceous (110 Ma). During the Early Tertiary (50 Ma), the source rock was highly mature for gas generation and at present-day, the charge is still active in the north offshore of Abu Dhabi.
The pre-Khuff charge history showed that the southern offshore and onshore structures are underfilled. The filling of these structures ranges between 50% and 80%, but in some onshore structures the filling is less than 50%. The middle and northern offshore structures are expected to be filled to spill point.
The Unayzah Formation in Abu Dhabi forms a potential target for future gas exploration. Many structures remain to be drilled especially in offshore Abu Dhabi and some of these prospects, may contain significant volumes of gas.
The facies variation, depositional environment, reservoir properties, and hydrocarbon potential of the Unayzah Formation were evaluated using data from key wells that are distributed over all Abu Dhabi (Figure-1). The data used in Unayzah evaluation included logs, drilling reports, selected cores and regional seismic lines. The available basin modeling results were incorporated into this evaluation. The Paleozoic basin modeling not only describes the maturation history of the Qusaibah source rock, but also predicts the filling percentage of the Abu Dhabi prominent fields.