A giant brownfield re-development project with long horizontal wells was initiated to arrest production decline mainly caused by a lack of pressure support and free gas influx from the large gas cap.
Key value drivers for the project are developing an understanding of the layers with regards to gas breakthrough, and achieving capital efficiency through low-cost well delivery, better planning and technology applications.
Firstly, the field has been segmented based on the analysis of multiple factors influencing the free gas production. It considers geological aspects such as the study of depositional environment and diagenesis, structural elements such as high permeability streaks and fractures, dynamic behaviors such as the water injection efficiency, gas cap expansion or coning.
Secondly, numerical simulations were then run in order to rank the sectors based on the expected model performance, compare them with real data categorization, and test the effect of the new proposed development schemes such as water injection at gas-oil contact and long horizontal wells equipped with downhole control valves.
It was found that each sector has a specific production mechanism and appropriate developments were recommended and then tested in the simulation. For instance, high permeability streaks play a significant role on the development of some sectors instigating a big difference of maturity between sub-layers, early water or gas breakthrough. Also, the inefficiency of water injection is one of the biggest issues of the field. Most of the water injectors are located too far from the oil producers, and have a low injectivity due to the often degraded facies in the aquifer because of diagenesis. This leads to a lack of pressure support that is counterbalanced by the gas injection, ending up with a lot of high GOR wells and a bad sweep from the top of the structure as the gas tends to by-pass the oil.
Simulation work showed that several remaining zones are safe for immediate development and should be prioritized for development in the near future. On the other hand, some of the mature layers prone to gas and water breakthrough need a boost for development, such as water injection at gas-oil-contact, artificial lift, low pressure system, GOR relaxation. Tight and undeveloped reservoirs are improved by implementing long horizontal drains.
When key geological scenario uncertainties, captured in multiple conceptual models, are combined with continuous parameters, the evaluation of a representative sample set quickly becomes unmanageable, laborious and too time consuming to execute. A workflow is presented that enables users to easily model conceptual as well as parametric uncertainties of the reservoir without the necessity of any complex scripting. The chain of models for all concepts is presented in one view, to provide overview of the key differences between concepts used. An ensemble of geologically sound samples can be created taking into account parameter dependencies and probabilities of concepts. The chain of models per concept can easily be (re)executed.
A case study is presented that consists of multiple concepts based on different hierarchical stratigraphic models in combination with different fault models, each of which with its own fluid- (defined contacts per compartment), grid- (sub-layering and areal resolution) and rock property models. Volumetric calculations are run on an ensemble to get static model observables like GRV, Pore Volume, Oil-In-Place, etc., reported by multiple sub-regions of the model in combination with a lease boundary. (When coupled with dynamic simulation, observables like ultimate recovery, break-through timing, etc. could also be obtained). As thousands of realizations were run concurrently, run time was reduced from weeks to hours. Results reveal the distribution and dependency of observables like GRV on top-structure-depth uncertainty and contact-level uncertainty. For in-place volumes the full suite of concepts and other parametric uncertainties including the stochastic uncertainties (i.e. seed) is analyzed. This also enables the identification of the key uncertainties that impact equity the most, which can be of great commercial value during equity negotiations. This workflow demonstrates how, with the power of Cloud computing, rigorous evaluation of multiple concepts combined with many parametric uncertainties has been achieved within practical turn-around times. As such it overcomes the prohibitive hurdles of the past that often have led to simplifications necessary to save time and effort. The result is better decision quality in resource development decisions.
Bigoni, Francesco (Eni S.p.A) | Pirrone, Marco (Eni S.p.A) | Trombin, Gianluca (Eni S.p.A) | Vinci, Fabio Francesco (Eni S.p.A) | Raimondi Cominesi, Nicola (ZFOD) | Guglielmelli, Andrea (ZFOD) | Ali Hassan, Al Attwi Maher (ZFOD) | Ibrahim Uatouf, Kubbah Salma (ZFOD) | Bazzana, Michele (Eni Iraq BV) | Viviani, Enea (Eni Iraq BV)
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.
The identification of the fluid fill history is a necessity for the development strategy of any field, in particular in the Middle East where tectonic history is often reported to affect fluid distribution and contacts in many fields. The fluid fill concept for a low permeability carbonate field has been re-evaluated and modified from a tilted contact interpretation with imbibition of the deepest unit to a field-wide flat contact and primary drainage saturation distribution. The oil volumes in the reservoir under study are sensitive to minor changes in the structure and fluid fill due to the relatively low structural dip and low permeability transitional nature of the reservoir. The paper highlights the importance of removing preconceptions in data analysis and ensuring consistency on interpretations between different available data sources. It also demonstrates how data quality could completely change the fluid fill concept.
The three main reservoir units of the Lower Shuaiba A, Lower Shuaiba B and Kharaib have been charged from two oil migration events. Structural changes post the first primary drainage are revealed by regional seismic images of the shallower horizons. Due to the rock low permeability, the water saturations are above irreducible value and the whole interval is in the "transition zone". Kharaib unit was believed to be imbibed by the aquifer after charge and was not developed. Three possible fluid fill scenarios were investigated: a) tilted contact due to structural changes post-charge, b) imbibition of the deeper interval, c) primary drainage with field-wide flat contact related to the second pulse of charge. Each scenario impacts the development of the three units positively or negatively. Water saturation logs vs. True Vertical Depth plots were the main diagnostic tool used to rule out fluid fill scenarios. The plots were used to recognise lateral changes of the saturation profile and investigate imbibition signatures. Production data were also used to cross check the expected fluid fill scenario. The resistivity tools’ types and mud resistivities were examined.
This paper presents a diagnostic workflow to understand and implement rock and fluid modeling in a diagenetically heterogeneous and hydrodynamically pressured Middle East carbonate field. The workflow allows interactive field data integration, provides guidance for reservoir property distribution and fluid contact generation in order to improve reserves and forecasting estimation. The workflow is useful to a reservoir modeler in QA/QC role and in this case it proves particularly applicable in an organization with constrained resources during the farm-in process. The workflow runs on numerical methods within the static model to avoid database discrepancy during the diagnostic process. Using the core (CCAL, SCAL), log and pressure database, the geoscientist can assess subsurface modeling outputs from the simplest to more complex deterministic scenarios. The process aims to minimize the discrepancy between data input and model output while continuously honoring the data, maintaining realistic correlations (e.g. between static permeability and water saturation) and respecting inherent uncertainty.
Using a data-rich Middle East carbonate reservoir, the pre- and post-diagnostic comparison of 3D modeled reservoir properties to the input data are demonstrated. Diagnostic steps have helped to understand potential subsurface scenarios and thus minimize the discrepancy post exercise. The value of the workflow is its ability to pinpoint the key uncertainties in rock and fluid modeling from the field’s vast dataset in a shorter diagnostic time. The application of the workflow in this carbonate reservoir case study increases the importance of geological and property driven rock type classification and its 3D distribution in matching the water saturation profile. This proved particularly challenging in this case study due to the field’s compartmentalization - fluid contact scenario.
Yonebayashi, Hideharu (INPEX CORPORATION) | Iwama, Hiroki (INPEX CORPORATION) | Takabayashi, Katsumo (INPEX CORPORATION) | Miyagawa, Yoshihiro (INPEX CORPORATION) | Watanabe, Takumi (INPEX CORPORATION)
CO2 injection is one of widely applied enhanced oil recovery (EOR) techniques, moreover, it is expected to contribute to the climate change from a viewpoint of storing CO2 in reservoir. However, CO2 is well known to accelerate precipitating asphaltenes which often deteriorate production. To understand in-situ asphaltene-depositions, unevenly distributed in composite carbonate core during a CO2 flood test under reservoir conditions, were investigated through numerical modelling study.
Tertiary mode CO2 core flood tests were performed. A core holder was vertically placed in an oven to maintain reservoir temperature and to avoid vertical segregation. A composite core consisting of four Ø1.5" × L2.75" plug cores, which had similar porosity range but slightly varied air permeabilities, was retrieved from a core holder after the flooding test. The remaining hydrocarbon was extracted by Dean-stark method, and heptane insoluble materials were extracted from each plug core via IP-143 method to observe distribution of asphaltene deposits. The variation of asphaltene mass in plug cores was investigated to explain its mechanism thermodynamically.
The core flood test was completed to achieve a certain additional oil recovery by 15 pore volume CO2 injection without any unfavorable differential pressure. The remaining asphaltene mass in each plug core revealed a trend in which more asphaltene collected from the inlet-side core. We assumed a scenario to explain the uneven asphaltene distribution by incorporating the vaporized-gas-drive and CO2 condensing mechanism. Namely, asphaltenes deposited immediately when pure CO2 contacted with oil. The contact between more pure CO2 and oil might be more frequently occurred in inlet-side core. To reproduce the scenario, a cubic-plus-association (CPA) model was generated to estimate asphaltene precipitating behavior as injected gas composition varied. In the first plug core, more pure CO2 gas was considered to contact with fresh reservoir oil compared with the downstream cores which might have less pure CO2 because of its condensation. The light-intermediate hydrocarbon gas vaporized by CO2 was also considered to emphasize the trend of more asphaltene deposits in upstream-side cores. The CPA model revealed consistent phenomenon supporting the scenario.
A flow simulation-driven time-lapse seismic feasibility study is performed for the Amberjack field that leverages existing multi-vintage 4D time-lapse seismic data. The focus is a field consisting of stacked shelf and deepwater reservoir sands situated in the Gulf of Mexico in Mississippi Canyon Block 109 in 1,030 ft of water. The solution leverages seismic interpretation, seismic inversion, earth modeling, and reservoir simulation [including embedded petro-elastic modeling (PEM) capabilities] to enable the reconciliation of data across multiple seismic vintages and forecast the optimal future seismic survey acquisition in a closed-loop. The overarching feasibility solution is integrated and simulation-driven involving multi-vintage seismic inversion, spatially constraining the petrophysical property model by seismic inversion, and performing reservoir simulation with the embedded PEM. The PEM is used to compute P-impedance and Vp/Vs dynamically, which enables tuning to both historical production and multi-vintage seismic data. The process considers a hybrid fine-scale 3D geocellular model in which the only upscaling of petrophysical properties occurs when the P-impedance from seismic inversion is blocked to the 3D geocellular grid. This process minimizes resampling errors and promotes direct tuning of the simulator response with registered seismic that has been blocked to a geocellular earth model grid. The results illustrate a three-part simulation-to-seismic calibration procedure that culminates with a prediction step which leads to a simulation-proposed time-lapse seismic acquisition timeline that is consistent with the calibrated reservoir simulation model. The first calibration tunes the model to historical production profiles. The second calibration reconciles the dynamic P-impedance estimate of the simulated shallow reservoir with that of the seismic inversion blocked to the 3D geocellular grid. The combination of these two steps outline a seismic-driven history matching process whereby the simulation model is not only consistent with production data but also the subsurface geologic and fluid saturation description. Large and short wavelength disparities in the P-impedance calibration existing between the simulator response and the time-lapse seismic data are attributed to resampling errors as a result of seismic inversion-derived P-impedance being blocked to the 3D geocelluar grid, as well as sparse well control in the earth model which leads to the obscuring of some asset-specific characteristics. The results of the third calibration step show how the time-lapse seismic feasibility solution accurately confirms prior seismic surveys undertaken in the asset. Given this confirmation, the solution achieves a suitable prediction of seismic-derived rock property response from the reservoir simulator as well as the optimal future time-lapse seismic acquisition time.
Hydrocarbon in place volumes are often inaccurate as a result of poor representation of the reservoir structure (by means of a 3D grid), that in combination with the use of traditional saturation calculation methods, lead to erroneous hydrocarbon volumes and poor investment decisions.
Traditionally a reservoir model is represented with a 3D grid, in a complex setting such as fault intersections and stacked reservoirs. A corner point grid is often used, which has limitations to represent this complexity. Further, the hydrocarbon saturations are then derived on a cell by cell basis on that 3D grid using simple averaging techniques of saturation height functions. The poor structure representation on the pillar grid in addition to the simplistic averaging methods lead to inaccuracies of the in place volumes especially where a prominent transition zone is present.
This paper presents new advanced saturation averaging methods (volume and height weighted) using saturation height functions on 3D grids. The new advanced saturation averaging methods are used on different reservoir models to compare the saturation distribution and volumetric differences against the traditional saturation calculation methods. A 4-way dip closure reservoir model with a tilted free water level (typical example of a carbonate reservoir in the Middle East), and a faulted S-grid model of the F3-FA field (North Sea) are used.
For the 4-way dip closure reservoir model, when comparing the advanced ‘volume weighted’ and traditional ‘by center of the part of the cell’ saturation averaging methods, a significant difference in the water saturations is observed which leads to about 5% difference in the calculation of in place hydrocarbon volumes. Further, it is observed that changing the thickness and orientation of the 3D grid cells can result in even larger differences of 5-10%.
The faulted F3 model shows that the difference between the hydrocarbon saturation values is largest where it matters most, that is, around the fluid contacts and in the transition zone. The new advanced saturation averaging methods give accurate hydrocarbon saturations irrespective of the size or complexity of the 3D grid and without any discretization effects.
Abdul Ghani, Mohamad (IFP Energies nouvelles) | Ayache, Simon Victor (IFP Energies nouvelles) | Batôt, Guillaume (IFP Energies nouvelles) | Gasser-Dorado, Julien (IFP Energies nouvelles) | Delamaide, Eric (IFP Technologies Canada Inc)
Although SAGD is a very popular in-situ extraction method in Canada, this thermal process relies on huge energy and water consumption to generate the steam. Irregular growth of the steam-chamber due to heterogeneities further degrades its yield. Contact between the steam chamber and the overburden also leads to heat losses. The objective of this paper is to investigate how Foam Assisted-SAGD could mitigate these technical issues and improve the efficiency of the SAGD process. Compositional thermal reservoir simulations are used to simulate and analyze a Foam Assisted-SAGD pilot. The shear-thinning effect close to the wells is also accounted for. The simulations are run on a homogeneous model mimicking the Foster Creek project in Alberta, Canada. Several type of injection sequences have been analyzed in terms of foam formation, back-produced surfactants and cumulative Steam-Oil-Ratio. Results are compared with the original SAGD performance. In order to propagate the foaming surfactants throughout the steam chamber the injection sequence needs to be properly determined. A simple continuous Foam Assisted-SAGD injection would lead to an accumulation of surfactant between the wells due to gravity segregation, preventing the foam from acting on the upper part of the steam chamber. Furthermore surfactant production occurs after a few weeks due to the proximity of the producer and the injector. A proper injection strategy of the type SAGD/slug/SAGD/slug is found to delay the chemical breakthrough and increase the amount of surfactant retained in the reservoir while allowing the surfactant propagation throughout the steam chamber. After optimization the Foam Assisted-SAGD process appears to be technically promising.
Al-Farisi, Omar (Khalifa University of Science and Technology) | Zhang, Hongtao (Khalifa University of Science and Technology) | Raza, Aikifa (Khalifa University of Science and Technology) | Ozzane, Djamel (ADNOC) | Sassi, Mohamed (Khalifa University of Science and Technology) | Zhang, TieJun (Khalifa University of Science and Technology)
Automated image processing algorithms can improve the quality and speed of classifying the morphology of heterogeneous carbonate rock. Several commercial products have worked to produce petrophysical properties from 2D images and with less extent from 3D images, relying on image processing and flow simulation. Images are mainly micro-computed tomography (μCT), optical images of thin-section, or magnetic resonance images (MRI). However, most of the successful work is from the homogeneous and clastic rocks. In this work, we have demonstrated a Machine Learning assisted Image Recognition (MLIR) approach to determine the porosity and lithology of heterogeneous carbonate rock by analyzing 3D images form μCT and MRI. Our research method consists of two parts: experimental and MLIR. Experimentally, we measured porosity of rock core plug with three different ways: (i) weight difference of dry and saturated rock, (ii) NMR T2 relaxation of saturated rock, and (iii) helium gas injection of rock after cleaning and drying.
We performed MLIR on 3D μCT and MRI images using random forest machine-learning algorithm. Petrophysicist provided a set of training data with classes (i.e., limestone, pyrite, and pore) as expert knowledge of μCT Image intensity correspondence to petrophysical properties. MLIR performed, alone, each task for identifying different lithology types and porosity. Determined volumes have been checked and confirmed with three different experimental datasets. The measured porosity, from three experiment-based approaches, is very close. Similarly, the MLR measured porosity produced excellent results comparatively with three experimental measurements, with an accuracy of 97.1% on the training set and 94.4% on blind test prediction.