Sun, Qian (Petroleum Engineering, Texas A&M University at Qatar) | Zhang, Na (Division of Sustainable Development, College of Science and Engineering, Hamad Bin Khalifa University) | Alyafei, Nayef (Petroleum Engineering, Texas A&M University at Qatar) | Wang, Yuhe (Petroleum Engineering, Texas A&M University at Qatar) | Fadlelmula, Mohamed (Petroleum Engineering, Texas A&M University at Qatar)
Reservoir simulation is commonly performed on upscaled models of complex geological models. The upscaling process introduces a principal challenge in accurately simulating two-phase fluid dynamics in porous media. To tackle this challenge, it is important to upscale relative permeability accurately. In this paper, a numerical method, which is based on the mimetic finite difference method (MFD) and digital rock analysis (DRA), is proposed for relative permeability upscaling. The validation of MFD is tested by two different cases with exact pressure solution. Then, the relative permeability of the digital rock (small element) is calculated based on the pore network modeling. The small elements are combined together to make up a larger model with different sizes (4×4×4, 6×6×6, 8×8×8, 10×10×10 elements). Finally, the accuracy of the proposed method is verified by comparing simulated results of the different sizes with that of the original one. The results show that MFD can solve the multi-phase flow scenarios with high accuracy and the
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.
A particular challenge inherent to carbonate reservoirs is reservoir rock typing which impacts model initialisation and saturation distributions and hence STOIIP, phase mobilities, and flow behaviours. We explore how flow diagnostics can be used best to detect subtle differences in reservoir dynamics arising from different model initialisations by comparing flow diagnostics simulations with full-physics simulations.
Flow diagnostics are applied to two reservoirs, a synthetic but realistic model representing an analogue for the Arab-D formation and a giant carbonate reservoir from the Middle East. Saturation modelling and reservoir rock typing is based on uniform and heterogeneous Pc and kr distributions, and further employs a state-of-the-art software that integrates of SCAL data and log-derived saturations. Sweep efficiency and dynamic Lorenz coefficients are then derived from the flow diagnostics results to quantify and compare the dynamic behaviour of the reservoir models. The full-physics simulations, which are used to validate the flow diagnostics results, are carried out with a commercial Black Oil simulator.
The flow diagnostics results can clearly distinguish between different homogenous and heterogeneous rock-type distributions, wettability trends, as well as novel saturation modelling approaches that use dedicated software tools. Flow diagnostics capture the same trends in recovery predictions as the full-physics simulations. Importantly though, the total CPU time for a single flow diagnostics calculation including model loading is on the order of seconds, compared to minutes and hours for a single full-physics simulation. These observation give confidence that flow diagnostics can be used effectively to compare and contrast the impact of reservoir rock typing, saturation modelling, and model initialisation on reservoir performance before running full-physics simulations. Flow diagnostic hence allow us to reduce the number of reservoir models from a model ensemble and select a small number of diverse yet realistic reservoir models that capture the full range of geological uncertainties which are then subjected to more detailed reservoir simulation studies.
Flow diagnostics are particularly well suited for complex carbonate reservoirs which are geologically more complex than clastic reservoirs and often exhibit significant uncertainties. Giant carbonate reservoirs are also challenging to simulate using full-physics simulators due to their size, so the impact of geological uncertainty on the predicted reservoir performance is often underexplored. Flow diagnostics are hence an effective complement to quantify uncertainty in state-of-the-art reservoir modelling, history matching and optimisation workflows, particularly for giant carbonate reservoirs.
This paper discusses the re-construction of the long-term development plan for an offshore giantfield located in Abu Dhabi with the aim to mitigate the rising challenges in the maturing field. The primary objective is to understand the reservoir behavior in terms of fluid movement incorporating the learning from the vast history while correlating with the geological features.
The field has been divided into segments based on multiple factors considering the static properties such as facies distribution, diagenesis, faults, and fractures while incorporating the dynamic behaviors including pressure trends and fluid movements.
On further analysis, various trends have been identified relating these static and dynamic behaviors. The production mechanism for each of the reservoirs and the subsequent sub reservoirs were analyzed with the help of Chan plots, Hall plots and Lorentz plots which distinctly revealed trends that further helped to classify the wells into different production categories.
Using the above methodology the field has been categorized in segments and color coded to indicate areas of different ranking. The green zone indicates area of best interest which currently has strong pressure support and wells can be planned immediately. The wells in this area are expected to produce with a low risk of water and gas. The yellow zone indicates areas of caution where special wells including smart wells maybe required to sustain production. This area showed relatively lower pressure support owing the location of the water injectors and the degraded facies quality between the injectors and the producers. The red zone highlights areas which are relatively mature compared to the neighboring zones and will require new development philosophy to improve the recovery. The findings from this study were used as the basis for a reservoir simulation study using a history matched model, to plan future activities and improve the field recovery.
This study involved an in-depth analysis incorporating the latest findings with respect to the static and dynamic properties of the reservoir. This has helped to classify the reservoir based on the development needs and will play a critical role in designing the future strategies in less time.
Contreras Perez, David Rafael (OMV E&P GmbH - Abu Dhabi) | Al Zaabi, Ruqaya Abdulla (ADNOC Offshore - GUL) | Viratno, Bernato (OMV E&P GmbH - Abu Dhabi) | Sellar, Christopher (OMV E&P GmbH - Abu Dhabi) | Susanto, Maria Indriaty (OMV E&P GmbH - Abu Dhabi)
This paper summarizes an efficient workflow for building a reliable static model reference case by improving the accuracy of well placement in a hydrocarbon bearing structure. This is beneficial in optimising upcoming well target position and trajectory planning as well as during the dynamic history matching process. In a non-operated venture, the ability to generate an up-to-date static model that maintains pace with operations, provides valuable insight to advise the operator on the upcoming drilling plan and continuously supports the dynamic model for reserves booking, is highly sought after.
The systematic approach described in this paper is applied to a geo-model from a Middle East carbonate reservoir consisting of over 50 wells with good quality PSDM seismic data. The workflow presented begins with seismic mapping, utilizing volume-based modelling techniques, followed by structural element correction using borehole images (e.g. structural formation dip and true stratigraphic thickness estimate) and finally introduces alternative control points, which enable drilled wellbore trajectories to be structurally anchored, based on layer thicknesses and structural trends within the target reservoir.
Using this approach it is possible to generate a consistent structural model that honours geological markers, measured dip ranges and structural trends seen from seismic data and image logs. During the process one learns more about data quality (e.g. scale of data resolution and depth of investigation), associated with specific fields and carbonate reservoirs through the interaction between geological, geophysical and petrophysical disciplines and ensures their correct use. Data are used to improve the raw interpreted seismic horizons by calibrating mapped thickness distribution against the well tops. 2D visualizations are generated on a well-by-well basis, including map views, curtain sections (along each horizontal well), composite cross-sections and 3D visualizations to show inter-well relationships within different geological layers. As a result the well is placed in the correct structural position. Correct well placement, especially of highly deviated/horizontal wells, provides more accurate identification of reservoir sweet spots, leading to improved well target position and trajectory planning for upcoming wells, and a robust baseline to achieve production/well test history match during the dynamic modelling process.
The traditional definition of volumetric sweep efficiency sums the effects of both fingering (arising due to contrasts in mobility) and bypassing (arising due to contrasts in permeability as well as well placement). Accordingly, we cannot quantitatively attribute poor sweep to either bypassing or fingering. Similarly, in EOR, the incremental recovery cannot be quantitatively associated with the reduction of those effects. For such purposes, we rely on visualization and mapping of saturation profiles to quantify and characterize the remaining oil in place including its distribution. . In this work, we propose a complementary method to obtain an instantaneous insight of the remaining oil distribution. We demonstrate the decomposition of fingering and bypassing effects and its utility. We first redefine recovery factors such that we decouple bypassing and fingering effects. We then validate those redefined sweep indicators by examining a 5-spot waterflood and two idealistic polymer floods. Later, we demonstrate the possible utility of those redefined sweep indicators through different examples. In one example, we compare the performance of a shear - thinning polymer to a recovery-equivalent Newtonian polymer. Using fingering and bypassing sweep indicators, we can immediately conclude that the shear-thinning polymer exacerbates bypassing. We recommend the adoption of our redefined sweep indicators in any simulation suite. They provide instant understanding of sweep and hence can be complementary to standard practices of oil saturation mapping and of special value when analyzing the results of multiple realizations and/or development scenarios.
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.
3D model is a valuable tool in reservoir management, provided its representativeness of reservoir dynamics.Traditional History Match mainly focuses on reproducing reservoir behavior at well scale. A good match is not always representative of fluid movements in the reservoir. The proposed approach for 3D model validation combines and compares the results of integrated production analysis, in particular flow paths identification, with history matching by using streamlines technology. Streamlines speed up the comparison process especially in complex 3D models.
The workflow is based on a massive Production Data Analysis (PDA) where geological and dynamic data are integrated to identify preferential paths followed by the different fluid phases during the producing life of the field. The main result is the Fluid Path Conceptual Model (FPCM) where aquifer and injected water movements are clearly identified. Once the flooded areas are detected, streamlines are traced on the history matched model in order to easily compare the simulated connections with hard information from PDA. Actions to improve the model representativeness are suggested and integrated in an iterative tuning process.
This paper presents the results of the methodology applied on two complex fields with different injection strategies. FPCMs resulting from PDA provided a powerful boost to drive the history match and speed up the whole process. Priority was given in reproducing the identified preferential paths rather than to perfectly match well production data (which can be also affected by allocation uncertainties) by means of local unrealistic adjustments.
Streamlines were run on Intersect simulation, proving to be a fast and powerful tool for the visualization and understanding of fluid movements in the 3D Model. Since streamlines are used as visualization tool and are traced on a corner point geometry grid using fluxes provided by reservoir simulation, the reliability of the simulation output is preserved.
Once the model is representative of the real field behavior, it can be used as predictive tool in Reservoir Management to optimize the current injection strategy, promoting most efficient injectors.