The Mishrif Formation is one of the important carbonate reservoirs in middle, southern Iraq and throughout the Middle East. In southern Iraq, the formation provides the reservoir in oilfields such as Rumaila/West Qurna, Tuba and Zubair. The top of the Mishrif Formation is marked by a regional unconformity: a long period of emersion in Turonian (ab. 4.4 My) regionally occurred boosted by a warm humid climate, associated to heavy rainfall. In Zubair Field, within the Upper interval of Mishrif Formation, there are numerous evidences of karst features responsible of important permeability enhancements in low porosity intervals that are critical for production optimization and reservoir management purposes. In the first phase, the integration of Multi-rate Production logging and Well Test analysis was very useful to evaluate the permeability values and to highlight the enhanced permeability (largely higher than expected Matrix permeability) intervals related to karst features; Image log analysis, on the same wells, allowed to find out a relationship between karst features and vug densities, making possible to extend the karst features identification also in wells lacking of well test and Production logging information. This approach has allowed to obtain a Karst/No Karst Supervised dataset for about 60 wells. In the second phase different seismic and geological attributes have been considered in order to investigate possible correlations with karst features. In fact there are some parameters that show somehow a correlation with Karst and/or NoKarst wells: the Spectral Decomposition (specially 10 and 40 Hz volumes), the detection of sink-holes at top Mishrif on the Continuity Cube and its related distance, the sub-seismic Lineaments (obtained from Curvature analysis and subordinately from Continuity), distance from Top Mishrif. In the light of these results, the most meaningful parameters have been used as input data for a Neural Net Process ("Supervised Neural Network") utilizing the Supervised dataset both as a Trained dataset (70%) and as a Verification dataset (30%). A probability 3D Volume of Karst features was finally obtained; the comparison with verification dataset points out an error range around 0.2 that is to say that the rate of success of the probability Volume is about 80%. The final outcomes of the workflow are karst probability maps that are extremely useful to guide new wells location and trajectory. Actually, two proof of concept case histories have demonstrated the reliability of this approach. The newly drilled wells, with optimized paths according to these prediction-maps, have intercepted the desired karst intervals as per the subsequent image log interpretation, which results have been very valuable in the proper perforation strategy including low porous intervals but characterized by high vuggy density (Karst features). Based on these promising results the ongoing drilling campaign has been optimized accordingly.
Karachaganak Field is an isolated carbonate bank consisting of Carboniferous to Lower Permian carbonate deposits located in the northern margin of the Pre-Caspian Basin of Kazakhstan. Discovered in 1979, it represents one of the largest gas and condensate reservoirs in the world and has been in production since 1985. This paper focuses on the different modeling methods applied to Late Visean sequence to try to improve the reservoir model reliability. In fact although this interval is relatively thin, it is mostly located inside the Oil Rim interval, so that it strongly impacts the present development phase which is focused on maximizing liquid recovery. This peculiar stratigraphic interval represents the highstand section of the Late Visean sequence and records the initial settling of micro-biohermal deposits constituted by in situ bryozoans, microbial boundstone, cementstone, all facies interlayered with crinoidal limestones. Due to its reduced thickness, there is a minimal contribution of the seismic sequence stratigraphy interpretation to understand the internal structure and geometry of this sequence. Despite its complexity, the Late Visean was initially modeled as a unique "undifferentiated body" characterised by the whole petrophysical data without discriminating the different depositional facies. Now, thanks to new core and analogue data, there is enough information to attempt to model this stratigraphic interval with a more detailed approach, trying to both reconstruct the 3D Facies distribution and utilize the relevant Reservoir Properties. Therefore two additional simulation methods have been tested: Object-Based Modeling and Multiple-Point Statistics Facies Modeling. Thanks to the long historical production, all these alternative scenarios have been compared to the initial SGS approach using the HM as benchmark to evaluate the best methodology to be applied.
Carbonate reservoirs are often characterized by karst features occurrence, usually related to a significant permeability enhancement in presence of low porosity and low permeability matrix type sediments. The distribution of such karst features is generally highly heterogeneous and difficult to predict, making the reservoir management challenging. In Zubair Field (Iraq), there are numerous evidences of karst events within the Upper interval of Mishrif Formation. The production behavior of Upper Mishrif is therefore very heterogeneous, moving from wells with relatively low flow capacity, as expected from petrophysical interpretation, to wells with a very high flow capacity, hence related to karst enhanced permeability. The integration of petrophysical interpretation, well test and multi-rate production logging allowed to preliminary highlight the improved permeability intervals associated to karst. In addition, accurate image log analysis on the same wells investigated a possible relationship between vug densities and production data, to be extended also to wells lacking the latter data. This process allowed to define a karst flag in more than 60 wells. Then, correlations between karst features and different seismic and geological attributes were identified. The most meaningful parameters were used as input data for a Neural Net Process, leading to the definition of a probability 3D Volume of karst occurrence. The final outcomes of the workflow are karst probability maps, used as a driver for the definition of new wells targets and associated trajectories. The recent drilled wells, with optimized paths according to these prediction-maps, have demonstrated the reliability of this approach intercepting the desired karst intervals. This study represents a valuable opportunity in terms of understanding of the reservoir behavior and impact on the ongoing intensive drilling campaign and related field performance.
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