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Africa (Sub-Sahara) Sonangol's deepwater Orca-1 well encountered oil in the presalt layer of Block 20/11 in the Cuanza basin offshore Angola. The well reached a measured depth of 12,703 ft. Initial well tests saw flow rates of 16.3 MMcm/D of gas and 3,700 BOPD. Cobalt International Energy (40%) is the operator, with partners Sonangol Research and Production (30%) and BP Exploration Angola (30%). Asia Pacific Premier Oil's Kuda Laut-1 well in Indonesia's Tuna production sharing contract has encountered 183 net ft of oil-bearing reservoir and 327 net ft of gas-bearing reservoir. Following evaluation operations, the well will be sidetracked to drill the Singa Laut prospect in an adjacent fault block. Premier is the operator (65%), with partner Mitsui Oil Exploration Company (35%).
The Prudhoe Bay field, located on the North Slope of Alaska, is the largest oil and gas field in North America. The main Permo-Triassic reservoir is a thick deltaic high-quality sandstone deposit about 500 ft thick with porosities of 15 to 30% BV and permeabilities ranging from 50 to 3,000 md. The field contains 20 109 bbl of oil overlain by a 35 Tcf gas cap. The oil averages 27.6 API gravity and has an original solution gas-oil ratio (GOR) of about 735 scf/STB. Under much of the oil column area, there is a 20- to 60-ft-thick tar mat located above the oil-water contact (OWC).
This paper describes a methodology to improve facies model robustness, by a systematic integration of well data ("hard" data) and outcrop analog studies ("smooth" data), both implemented as conditioning data in alternative numerical methods. The methodology presented is illustrated by a case study of a fluvial reservoir analog in the Triassic of the Lodeve basin (France).
On this example, most of reservoir grids are populated by kriging-based stochastic algorithms, supported by geostatistical tools controlling lateral continuity, vertical organization, or simple facies organization. If these tools are sufficient to handle simple environments with smooth facies transitions, all are deeply affected by sampling, giving a skewed representation of sedimentological model and consequently, a skewed numerical model. Moreover, these statistics-based methods are generally inefficient to represent complex fluvial systems. If well data and geostatistical tools are necessary to elaborate a robust conceptual model, a secondary constrain must be used in parallel to better handle characteristics of depositional system.
The methodology developed here is reviewing the fundamental steps of facies modeling process: data analysis, conceptual model elaboration coupled with a "back to outcrop" process and finally, the numerical implementation and it associated quality control procedures. This study is supported by an exhaustive dataset, with 6 drillholes including one cored (42m), conventional welllog data (6), GeoRadar profiles (10 lines), CCAL (>150 samples) and supported by a full outcropping cliff of 200m length. The systematic data review allow to define which facies can be identified at well, how these facies are vertically stacked in the well and how they evolve laterally. These observations help to harden a conceptual sedimentological model able to predict the facies partitionning enhanced by hydraulic mechanisms. To fill the gap between concept elaboration and facies modeling implementation, a "back to outcrop" is fundamental to provide critical elements, directly impacting the robustness of geological models. This includes (but not limited to) geobodies dimension, interaction, preservation, at an intermediate scale between wells (<1m) and seismic (>50m). Finally, these observations will be implemented as external constrain in a concept-based algorithm (nested Boolean, Multi-point statistic), to capture more precisely the rules governing the depositional model.
The final critical step consists in discussing the strengths, limitations and uncertainties associated to these alternative methods. Indeed, the back-to-outcrop process acts as an absolute quality control procedure, highlighting where algorithms or methods are not sufficiently constrained to capture the depositional model. The observations extracted during this process allow a continuous improvement, with the final objective to improve drastically the geological model robustness, and it associated forecasts.
Vaisblat, Noga (University of Alberta) | Rangriz Shokri, Alireza (University of Alberta) | Ayranci, Korhan (University of Alberta) | Harris, Nick (University of Alberta) | Chalaturnyk, Rick J. (University of Alberta)
This paper presents a critical insight into evaluation of elastic properties of the Montney Formation siltstone through indentation measurements and log-derived elastic moduli, including Young’s modulus, Poisson’s ratio, and brittleness. Further, we explored the relationship between geomechanical properties and rock fabric, mineralogy, and its role in hydraulic fracturing treatments.
We examined seven wells along a northwest-southeast cross-section, sub-parallel to basin dip. Facies analysis was conducted on four long Montney cores (70 to 250 m). Young’s modulus, Poisson’s ratio, and brittleness were calculated from dipole sonic and density logs. Where shear sonic log was not available, predictions of shear wave velocity were performed from near-by wells. Hardness profiles of core samples, measured by a hand-held indentation device, were compared with rock composition from QEMSCAN (mineralogy) and LECO-TOC (organic matter). A coupled hydro-mechanical code, capable of explicit inclusion of lithofacies variation and bedding discontinuities, was employed to investigate the response of the siltstone to hydraulic fracture propagation in the Montney formation.
A comprehensive facies analysis revealed 16 lithofacies across the basin, with depositional environments ranging from tidal flat to offshore sediments, and deep-water turbidite deposits. The variations of Young’s modulus, Poisson’s ratio, and relative brittleness from well logs were compared against indentation measurements of the four long cores and against rock composition in all wells. Young’s modulus, brittleness, and hardness showed similar trends in each well, while Poisson’s ratio demonstrated a trend with depth opposite to all other elastic parameters. No clear distinction was found between the geomechanical properties of different lithofacies in each well. More importantly, similar lithofacies commonly exhibit significantly different geomechanical properties in different wells. The analysis from coupled numerical simulations also confirmed that effective fracture propagation was not necessarily lithology controlled; rather it was greatly constrained by geomechanical contrasts. Further statistical analysis indicated that clay content, and to a lesser extent organic matter content, had the strongest control on elastic moduli in the Montney Formation, reducing Young’s modulus, brittleness, and hardness, but increasing Poisson’s ratio.
Our study concludes that unlike other unconventional reservoirs, geomechanical properties in the Montney Formation are not lithofacies-dependant. We attribute the weak influence of depositional environments on the sediment to the size and compositional homogeneity of detrital material that entered the basin. Clay minerals and organic matter were identified as controlling factors on elastic moduli -and thus hydraulic fracture propagation- in the Montney Formation.
Zhao, Huawei (Sinopec Petroleum Exploration and Production Research Institute) | Zhao, Tianyi (Sinopec Petroleum Exploration and Production Research Institute) | Hou, Tengfei (CNPC Engineering Technology R&D Compnay Limited) | Lian, Peiqing (Sinopec Petroleum Exploration and Production Research Institute) | Shang, Xiaofei (Sinopec Petroleum Exploration and Production Research Institute) | Li, Meng (Sinopec Petroleum Exploration and Production Research Institute) | Zhang, Wenbiao (Sinopec Petroleum Exploration and Production Research Institute) | Wu, Shuang (Sinopec Petroleum Exploration and Production Research Institute) | Duan, Taizhong (Sinopec Petroleum Exploration and Production Research Institute)
Integrated characterization methods from micro-scale to macro-scale were applied to thoroughly study the petrophysical properties of the Upper Triassic Xujiahe fractured tight gas reservoirs. The lithology, pore types, pore structure, and porosity-permeability relationship were described based on experimental results of thin section analysis, computer tomography, and porometer and permeameter. And special attention was paid to characterize the natural fractures, and try to unveil the effects of fracture on gas storage and transportation. A dual-porosity dual-permeability (DPDP) dynamic model of well L150 was established, and the effects of natural fractures on the productivity were studied.
The lithology is mainly lithic arkose, feldsparthic litharenite, and litharenite. The formation is highly tight due to compaction and cementation during the early and middle burial stages, and only some interparticle pores and grain dissolution pores remained. Fractures are classified into two types, which are structural fractures and interlayer fractures. The first type is caused by tectonic movement, and is mainly developed in siltstone and fine sandstone; while the second type is developed between coarse sandstone beddings. Mercury injection capillary pressure experiment reveals that the pore size of the tight sandstone is 2-200 nm. The porosity of the samples is in the range of 2%-6%, and the permeability is 5 ×10-3-1×10-1 mD. Yet the permeability of some samples may be as large as 1000 mD because of the micro fractures. Results of history matching and production predictions of the dynamic model indicate that natural fracture is the important to natural gas production.
Menon, Pradeep (ADNOC Upstream) | Anurag, Atul (ADNOC Offshore) | Mills, Carey (ADNOC Upstream) | Basioni, Mahmoud (ADNOC Upstream) | Steiner, Stefan (ADNOC Upstream) | AlBlooshi, Mohammed (ADNOC Upstream) | Dasgupta, Suvodip (Schlumberger) | Guerra, Julian (Schlumberger) | Shasmal, Sudipan (Schlumberger) | Adil Suliman Salim, Israa (Schlumberger)
The Khuff Formation is a Permo-Triassic aged carbonate unit which reservoirs a highly economic gas resource in several countries within the Middle East. The appraisal and development of Khuff Formation tight gas resources is the subject of increased focus in the offshore UAE. This case study focuses on the appraisal of a particular field in offshore Abu Dhabi and summarizes how the understanding of this complex reservoir has evolved over time.
The oldest well penetrating the Khuff Formation in this field was drilled almost 3 decades ago. This well tested gas within the Upper Khuff however appraisal of this resource had to wait until 2017-18 when two appraisal wells were drilled on the discovery. These appraisal wells included a complete suite of wireline logs, image log data, formation pressure measurements and well tests to give a clearer picture of the formation and fluid saturations. Subsequent to the drilling of the recent appraisal wells an integrated study was completed integrating all the processed and advanced answer products in order to determine the key elements controlling gas productivity. This knowledge were subsequently applied to optimise a well drilled and production tested in late 2018.
Understanding the production behavior of the Khuff Formation reservoirs intervals has been one of the most critical factors behind the decision to develop this complex reservoir. Certain key answer products are considered critical for identification of completion intervals. These products include; sonic imaging (looking for fractures away from the wellbore), advanced textural analysis from borehole images (porosity classification) and critically stressed fracture analysis from geomechanics. This study led to the conclusion that critically stressed fractures and/or connected pores from images are the best indicators of high gas flow potential, while this flow can become exponentially higher when fractures at the wellbore connect to fractures away from the wellbore. This workflow has now been applied to the most recently drilled well and to other Khuff Formation appraisal projects across the off shore of Abu Dhabi.
This is an illustration of how in-depth analysis of all the acquired data in an integrated manner can help in understanding a complex reservoir and lead to better decision-making for the future wells and offset appraisal projects. Lessons are hidden in both success and failure and as long as these lessons are analyzed properly, they can lead to long-term success.
Feng, Cheng (China University of Petroleum-Beijing at Karamay) | Li, Jiahong (Research Institute of Petroleum Exploration and Development, PetroChina) | Feng, Ziyan (China University of Petroleum-Beijing at Karamay) | Zhong, Yuntao (China University of Petroleum-Beijing at Karamay) | Zhang, Ning (China University of Petroleum-Beijing at Karamay) | Mao, Zhiqiang (China University of Petroleum-Beijing)
For no natural productivity, hydraulic fracturing is widely used in unconventional reservoirs. Thus, oil production prediction before hydraulic fracturing is crucial. In general, it is usually obtained based on percolation theory and fracture geometrical model from engineering data. However, before hydraulic fracturing, the obtained data are mainly geological and petrophysical data. Hence, predicting oil production from them before hydraulic fracturing can make a lot of sense for guiding fracturing design. Although geological and petrophysical data have complex and nonlinear relation with oil production after hydraulic fracturing, least squares support vector machine (LSSVM) is very suitable for such high-dimensional and nonlinear problem with small datasets. As the performance of LSSVM highly depends on parameter selection, an improved LSSVR is designed based on particle swarm optimization (PSO). The selected study area is tight oil reservoirs of Chang 8 Formation, Triassic, Ordos Basin, China. In order to build a reliable data-driven oil production prediction model, a systematic formation evaluation workflow is proposed. Firstly, choose wells with similar hydraulic fracturing type in the study area, which is the base. Secondly, the oil production prediction problem is converted into a classification problem by dividing the oil production into four levels. Thirdly, the dataset of 24 geological, petrophysical and engineering parameters from 85 wells are selected and constructed, reflecting lithology, physical property, saturation, rock mechanics, thickness and facies. Fourthly, 8 parameters, including density, the difference of neutron and density porosity, permeability, water saturation, effective thickness, Poisson's ratio, interlayer stress difference and displacement amount, are optimized as sensitive ones by principal component analysis (PCA). Fifthly, the data from 85 wells are separated into two categories: training and testing data, according to the proportion of 70% and 30%, respectively. The former are used to train the model, while the latter are used for verification. Sixthly, the improved PSO based LSSVM and the LSSVM are trained and tested via the dataset respectively. The tested results present that the coincidence rate of the prediction of the two methods are 88.06% and 81.16% respectively. This work verifies that predicting oil production from geological and petrophysical data before hydraulic fracturing via an improved LSSVM is feasible and cost-effective, which can be important for guiding fracturing design and providing scientific basis for deployment of development program.
Menon, Pradeep (ADNOC Upstream) | Steiner, Stefan (ADNOC Upstream) | Mills, Carey (ADNOC Upstream) | Basioni, Mahmoud (ADNOC Upstream) | Mosse, Laurent (Schlumberger) | Dasgupta, Suvodip (Schlumberger)
The Permo-Triassic Formation of Khuff in offshore Abu Dhabi has shown a considerable potential as a tight gas reservoir, but the complex mineralogy and the heterogeneity has made formation evaluation challenging for this reservoir, particularly in respect to saturation. Complexities with log interpretation in these tight formations have called for the use the advanced measurements to help interpret more basic logs in a simple but accurate and consistent manner.
Deriving porosity from density requires the knowledge of matrix density. In complex Khuff reservoir, with a varying mix of dolomite and anhydrite with some calcite, it is impossible to put a constant matrix density. Photoelectric factor is not enough to resolve the mineralogy and advanced spectroscopy measurement is mandatory to provide matrix properties such as grain density, neutron (thermal and epithermal) and sigma (capture cross-section). These properties are used to compensate the formation density, neutron and sigma for the matrix effect, focusing any residual separation between the corrected porosities onto fluid effects.
Matrix-corrected density, neutron and sigma porosity curves can be used effectively to qualitatively interpret presence of gas, which is a big challenge in these tight gas reservoirs and this approach is demonstrated on multiple datasets. Since this is being applied on wireline logs with a depth of investigation shallower than 10-in, uncertainties remain concerning the deep, uninvaded zone water saturation. The deep resistivity measurement is still the only access to deep saturation. To quantify the water saturation from resistivity, besides the knowledge of formation water salinity, the other key information is the Archie parameter m (cementation exponent), which is directly dependent on the texture of the rock. Complex diagenesis on the varying mineralogy of the Khuff has created complex water-phase tortuosity, which needs to be considered. Multi-frequency dielectric measurement in addition to giving a shallow zone water saturation, also provides a water-phase tortuosity parameter, which is then used to improve deep water saturation computation.
When facing a complex reservoir, the temptation is high to jump to complex evaluation workflows, neglecting simple, quick-look-type approaches. However, advanced measurements, such as spectroscopy and dielectric dispersion empower this type of simple approach, enabling efficient controls and insights on the evaluation, as will be shown through the examples in this paper. Final evaluation still requires a fully integrated analysis, but it will benefit from the lesson learnt and insights from the quick-look.
Gondalia, Ravi Ramniklal (Schlumberger) | Kumar, Rajeev Ranjan (Schlumberger) | Zacharia, Joseph (Schlumberger) | Shetty, Varun (Schlumberger) | Bandyopadhyay, Atanu (Schlumberger) | Narayan, Shashank (Schlumberger) | Bordeori, Krishna (Schlumberger) | Singh, Mukund Murari (Schlumberger) | Shah, Arpit (Schlumberger) | Choudhary, Dinesh (Schlumberger) | Sharma, Lovely (Schlumberger) | Ray, Maria Fernandes (Schlumberger) | Sarkar, Samarpita (Schlumberger) | Moulali, Shaik (Oil and Natural Gas Corporation Limited) | Das, Santanu (Oil and Natural Gas Corporation Limited) | Rao, Dasari Papa (Oil and Natural Gas Corporation Limited)
The Triassic–Jurassic petroleum system reserves in Krishna Godavari Basin are found at 3500 to 4500 m depth with bottomhole static temperature (BHST) ranging from 270 to 340°F. Hydraulic fracturing is required to produce economically from these wells because the in-situ permeability of these sands is in the range of ~ 0.01 md. Hence, after perforations, minimal production is observed or the flash production from these wells dies out in a short time span.
Between 2010 and 2017, several appraisal wells were drilled and completed using hydraulic fracturing in the onshore Krishna Godavari Basin. However, the success rate of effective fracture placement and sustained production enhancement due to hydraulic fracturing was limited. This was attributed to insufficient understanding of rock mechanical properties and lack of a refined fluid fracturing system despite using a superior fluid system like carboxymethyl hydroxypropyl guar (CMHPG) with organometallic zirconate-based crosslinkers.
In 2018, nine wells were successfully hydraulically fractured, and sustained production from these wells was established using a simple borate-based crosslinked fluid system. A key change for the field was rather than designing and pumping fracturing fluid based on only BHST, one of the critical components that led to better proppant placement is the stable fracturing fluid that was fine tuned for the well based on factors like change of source water, tubular shear exposure time for designed fracturing treatment pumping rate, and hydrocarbon properties. This combination of rock mechanical properties and fracturing fluids used is captured as the efficiency of the fluid system, and this governed the usage of fluid loss additives, again a novel introduction for the field. Finally, the key to producing these sands was adequate cleanup and minimal guar residue to maximize the proppant pack conductivity. The paper also discusses the strategy to design fluids with minimal guar loading to reduce polymer retention and to achieve maximum fracture fluid recovery. This robust management of fracturing fluids along with understanding of rock mechanical properties can be seen in the post-fracturing production results.
Sonangol's deepwater Orca-1 well encountered oil in the presalt layer of Block 20/11 in the Cuanza basin offshore Angola. The well reached a measured depth of 12,703 ft. Initial well tests saw flow rates of 16.3 MMcm/D of gas and 3,700 BOPD. Cobalt International Energy (40%) is the operator, with partners Sonangol Research and Production (30%) and BP Exploration Angola (30%). Premier Oil's Kuda Laut-1 well in Indonesia's Tuna production sharing contract has encountered 183 net ft of oil-bearing reservoir and 327 net ft of gas-bearing reservoir.