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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%).
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.
Erzuah, Samuel (University of Stavanger and The National IOR Centre of Norway) | Fjelde, Ingebret (NORCE Norwegian Research Centre AS and University of Stavanger) | Omekeh, Aruoture V. (NORCE Norwegian Research Centre AS and The National IOR Centre of Norway)
Wettability controls the fluid-phase distribution and flow properties in the reservoir. The ionic compositions of brine, the oil chemistry, and the reservoir-rock mineralogy have profound effects on wettability. Wettability measurement can be obtained from special core analysis (SCAL), but those data are not readily available, and the cost and time of analyzing different possible injection waters can be excessive. There is thus a need for early evaluation of wettability because it is crucial for selecting optimal field-development options. Information about wettability can be indirectly obtained from logging of other rock properties, but the uncertainty in the estimated wettability range is often high. In addition, wettability alteration by injection brines cannot be analyzed by logging. This study seeks to estimate the wettability by assessing the electrostatic interactions existing between the mineral/brine and the oil/brine interfaces using a surface-complexation model (SCM) supported with relatively simple and fast flotation experiments.
The SCM is a chemical equilibrium technique of characterizing surface adsorption phenomenon. The SCM provides a cost-effective technique of characterizing the wettability of minerals at reservoir conditions. Ionic composition of the brine and the properties of the minerals were used as input to the model. In addition, the polar oil components in the crude oil were converted into their equivalent organic acid and base concentrations to be incorporated into the model. The electric-double-layer model that was used in the SCM was the diffuse-layer model. The SCM simulation is a fast and inexpensive wettability-characterization tool if reservoir cores and crude oil required in conventional wettability measurements are not readily available.
From the flotation and SCM results, it could be concluded that the latter could capture the oil-adhesion tendencies of the former. Not only does the SCM predict the wetting tendencies of the minerals, but also it has the capacity to evaluate the mechanisms that led to their wetting preferences. For instance, the SCM results reveal that for negatively charged mineral/brine and oil/brine interfaces, divalent cations such as Ca2+ and Mg2+ can serve as a bridge between the two interfaces, thereby leading to oil adhesion. On the other hand, for positively charged mineral/brine interfaces such as calcite, direct adsorption of the carboxylic oil component was the dominant mechanism for oil adhesion. The SCM technique of characterizing wettability can be used to screen possible injection-water compositions to assess their potential to alter the wettability to more water-wet. Finally, the SCM technique could capture the trend of f-potential measurements from literature.
In this paper we propose a new workflow to perform Petrophysical Joint Inversion (PJI) of surface to surface seismic and Controlled Source ElectroMagnetic (CSEM) data, to recover reservoir properties (clay volume, porosity and saturation). Seismic and CSEM measurements provide independent physical measurements of subsurface that complement each other. In the case of well-logs, the basis of the PJI training dataset, taking advantage of such complementarity is straightforward. Indeed, elastic and electric measurements of earth properties sense the same earth volume at much the same scale. When applying the training dataset to the surface data derived geophysical attributes, the order of magnitude gap in between the scale at which those elastic and electric attributes represent the earth undermines dramatically PJI validity. Various CSEM inversion constraining methods (regularization breaks, prejudicing, use of an a priori model etc) help to reconcile seismic and CSEM resolution, but they are usually proven to be insufficient or inaccurate. In addition to these methods, we suggest adding a further downscaling step, so the recovered electric attribute resolution can be adequate with respect to the seismic one, hence fit for purpose. Such downscaling is designed to be consistent in electrical attribute space via transverse resistance within a rockphysics framework. The workflow will be demonstrated on a case study.
Well tests for smart, horizontal wells in faulted and heterogeneous reservoirs with complex fluids and uncertain contacts are nearly impossible to design and interpret with geological consistency using traditional analytical methods. Such cases lend themselves to numerical reservoir simulation, but the number of uncertain parameters and their interaction can make design difficult and the interpretation process time-consuming. We used an uncertainty-based technique for test design and interpretation with numerical models for a test in the Norwegian Barents Sea. We describe a new global sensitivity analysis methodology to determine how the interaction of multiple uncertain reservoir parameters (such as water contact depth, fault transmissibility, reservoir permeability, and anisotropy) influences the uncertainty in the pressure derivative response. With time-dependent plots of parameter sensitivity, confident decisions can be made about the test duration and the ability to address test objectives.
Our methodology shows how exploration of the full range of reservoir uncertainty gives confidence in the expected flowing conditions, which are used to manage operational risks. The results of the design study, which are fully-integrated with the geological and geophysical description of the reservoir, are used during real-time monitoring and final interpretation. The full methodology was applied for the first time to a well test targeting the shallow Mid-Jurassic Stø Formation in Wisting discovery, the northernmost oil discovery situated in the Hoop area of the Barents Sea. The test design clearly indicated that water breakthrough was not expected but that gas production could not be ruled out given the range of uncertainty of the reservoir parameters.
The test was monitored in real time. From the hundreds of cases produced and analyzed, matches were obtained during monitoring to give an indication of the future behavior of the well during the final buildup. This helped to dictate the test plan and buildup duration.
As predicted, interpretation of the final derivative was challenging due to reservoir complexity. Traditional analytical interpretation could easily have suggested sealing faults in the near-well vicinity. However, using an amalgamated numerical model derived from the initial real-time matches and then further calibrated to the test data, we provided an interpretation of all the data obtained during the test, including matching the liquid ratios and accounting for wellbore dynamics. We not only achieved a good pressure and pressure derivative match with a model coherent with the geology, but also confirmed connected volumes.
Accurate wettability estimation is essential in optimizing oil production, because it controls the fluid phase distribution and flow properties in the reservoir. The ionic composition of the brine, the oil chemistry and the mineralogy of the reservoir rock are believed to have weighty effect on the wettability. In this study, the objective was to estimate the wettability by Surface Complexation Modelling (SCM). The simulation results were confirmed by the findings from their corresponding wettability estimation using the flotation technique. Quartz, kaolinite and calcite minerals were selected for this study because they dominated the compositions of the studied reservoir rock. Both the SCM and the flotation test results elucidate the role of the reservoir rock mineralogy, the composition of the Formation Water (FW) and the oil chemistry on wettability estimation. The simulation results show that quartz is strongly water-wet while calcite is also strongly oil-wet which is consistent with the flotation test results. The kaolinite on the other hand was less water-wet as compared to quartz but more water-wet as compared to calcite. The SCM results show that oil adhesion is due to bridging by divalent ions when the mineral surface and oil-brine interface have similar charge. The oil adhesion was observed to increase with increase in divalent ion concentration. For positively charged mineral surface such as calcite, direct adsorption of carboxylic acid was the dominating mechanism for oil adhesion. Nevertheless, divalent ions bridging mechanism also occurred for the electrostatic pair linkages in calcite. From the simulation results, it can be concluded that the surface charge of the mineral has an overriding effect on oil adhesion compared to the oil-brine interface. To add to the above, the carboxylic acid has a huge influence on the wetting properties of the minerals than the basic counterpart. This is mainly due to pH of the studied systems. SCM provides a cost-effective technique of estimating the wettability of minerals at reservoir conditions. Finally, the SCM approach of characterizing the wettability can be used to screen possible injection water compositions to assess their potential to alter the wettability of the reservoir rock surface to more water-wet. Thus, compelling the adsorbed oil to be released, mobilized and produced with the injected water.
Pongtepupathum, W. (Imperial College London) | Williams, J. (British Geological Survey) | Krevor, S. (Imperial College London) | Agada, S. (Imperial College London) | Williams, G. (British Geological Survey)
This paper focuses on pressure management via brine production optimisation to reduce reservoir pressure buildup during carbon dioxide (CO2) sequestration using a geocellular model representing a sector of the Bunter Sandstone Formation. The Bunter Sandstone is a deep saline aquifer with high reservoir quality and is a leading candidate for potential CO2 capture and storage (CCS) in the UK. Brine production optimization during CO2 sequestration is necessary because it helps minimize brine waste and well construction and operational costs. In this paper, various sensitivity analyses were performed investigating well geometry, injection and production well spacing, pressure management and boundary condition effects. Two scenarios were investigated and development plans were proposed for annual injection of 7 MT/yr CO2 (Scenario 1), which is equivalent to the CO2 emissions of a 1.2 GW coal-fired power plant, and for scenario 2, where we aim to utilize the maximum storage capacity of the reservoir model. Three pressure management schemes were compared for each scenario: no pressure management or no brine production, passive pressure management where pressure relief holes are drilled and brine passively flows to seafloor without external energy, and active pressure management where brine is actively pumped out. Brine production rate and relief well patterns were evaluated and optimised. The results show that well perforation length and the use of deviated wells have a significant impact on injectivity improvement whereas well radius has little impact on injectivity. Symmetrical well placements between injection and production wells yields higher storage capacity than asymmetrical ones, and increasing the number of relief wells improves CO2 storage capacity. In the case of open boundary conditions, no pressure management is required because the reservoir quality enables pressure dissipation, resulting in a pressure buildup of less than 5 bars. In the case of closed boundary conditions, either passive or active pressure management is required to prevent seal failure from overpressurization of the reservoir and it also increases storage capacity. The cases with open boundaries, as expected, yield higher storage capacity than the cases with closed boundaries. In scenario 1, or assumed annual injection of 7 MT, storage capacity is 344 MT without pressure management and with open boundaries. This is compared to 332 and 328 MT for cases with closed boundaries and passive and active pressure management, respectively. In scenario 2, the maximum storage capacity of the model is 684 MT with no pressure management and open boundaries, and 504 and 683 MT with closed boundaries with passive and active pressure management, respectively. The storage efficiency ranges from 1 to 6% in scenario 1 to the highest at 12% in the maximum storage capacity case. In addition, three aquifer sizes; open boundary aquifer size of 2.43×1012m3, an aquifer size of 1.8×1010m3 based on pressure recharge studies of the Esmond Gas Field, and closed boundary aquifer size of 1.22×1010m3, were compared for the optimised cases. The study shows that aquifer size has an impact on estimation of CO2 storage capacity. The storage capacities of the three aquifer size cases ranging from the largest to smallest without pressure management are 344, 105 and 74 MT, respectively.
The Goliat field development is challenging because of its extreme and remote environment in Barents Sea. The field consists of two separate main reservoirs, Realgrunnen and Kobbe, both having complex structural setting with a high number of faults and considerable reservoir heterogeneity. In order to maximize production, producer wells usually navigate through several sand sequences. In addition, proximity to oil-water-contact (OWC) in the Kobbe formation has to be considered to avoid early water break through.
Eni Goliat team selected deep directional resistivity reservoir mapping LWD technology for geosteering and detecting payzone remotely. Being able to map multiple formation layers away from the wellbore, the service helped G&G team to optimize well paths during drilling to achieve the target sand exposure in the different sequences.
The results presented here on both the Realgrunnen reservoir and Kobbe reservoir were excellent. The producer well C was successfully geosteered in the upper sands in Realgrunnen reservoir, achieving a NTG of 70% despite the presences of subseismic scale faults and lateral facies heterogeneities along the well.
For the producer well E in the Kobbe reservoir, although the well was landed deep and close to OWC because the top reservoir came 11 meter deeper than prognosis, the accurate mapping of the top reservoir, OWC, and optimizing the well path, helped to support the decision to build aggressively and level out at optimal TVD, achieving 340 meters in the Kobbe 9 sand.
This communication will present also how cautious and in-depth evaluation, extensive pre-drilling study and operation planning enabled efficient geosteering of the horizontal producers in this challenging environment and maximizing productivity delivered. Post drilling, the mapping of the reservoir structure and fluid contacts were used as inputs to the static model and integrated into future development plans.
Estimation of reservoir rock and fluid properties is highly dependent on the parameters used in the rock physics models. Determining water saturation is very important to estimate hydrocarbon reserves and is often computed using Archie’s equation. Any uncertainty associated with the parameters in the Archie model as well as resistivity of clay in shaly sand formations may cause errors in the estimation of petrophysical parameters. It is very important to evaluate the relative impact of these parameters on reservoir rock and fluid properties. In this work, a series of sensitivity tests were carried out in order to investigate which of the formation water resistivity
Presentation Date: Wednesday, October 19, 2016
Start Time: 2:45:00 PM
Presentation Type: ORAL
Electrical anisotropy has a strong effect on CSEM data (Ramananjaona et al, 2011), and understanding this effect is key in ensuring robust survey design and well constrained data analysis (MacGregor & Tomlinson, 2014). Electrical anisotropy can also provide key information that can be used to understand regional variations in rock physics properties as well as provide possible indications to geological drivers in an area, such as uplift. To date there have been no systematic regional studies of electrical anisotropy in background geological structure. Addressing this need, by investigating electrical anisotropy variations across the Barents Sea is one of the main goals of the industry funded ERA consortium.
Bulk anisotropy values were derived from CSEM data for each of the major stratigraphic units across the Barents Sea. This was achieved by performing 1D anisotropic inversion of CSEM data acquired around well bores, and tying the horizontal resistivity to the induction log measurements from these wells. Results were then mapped and regional trends are investigated. The modelling confirms the presence of high electrical anisotropy ratios in the Barents Sea area and a correlation between anisotropy ratio and formation age: In general the older the formation, the higher the anisotropy ratio. Although resistivity varies regionally, the variation in anisotropy ratio is less pronounced.
The anisotropy analysis covers multiple Barents Sea areas and includes 20 drilled wells. The wells included in this study have been subdivided in 10 different groups based on their geographical location (Table 1). Note that in area 10 (Hoop) no wells were available, and results are based solely on CSEM data. For each area CSEM data were inverted to determine resistivity and anisotropy values.