Transmitting electrical current to the subsurface can create special considerations. Successful application of electromagnetic heating often requires a multi-disciplinary approach combining electric engineering and petroleum engineering. To assist petroleum engineers considering this approach, this article identifies some of the issues that an electrical engineer might normally anticipate and address. In most practical situations, we are concerned with fields that vary periodically in time (the sinusoidal steady state generally). In these cases the electrical phenomena are properly described by Maxwell equations in terms of complex vector field intensities of electric and magnetic fields (E and H); complex vector field electric, magnetic, and current densities (D,B,J); complex charge concentrations (ρc); and complex material parameters: conductivity, permittivity, and permeability (σ, ε, μM).
Yong, Wen Pin (PETRONAS Research Sdn. Bhd.) | Azahree, Ahmad Ismail (PETRONAS Research Sdn. Bhd.) | M Ali, Siti Syareena (PETRONAS Research Sdn. Bhd.) | Jaafar Azuddin, Farhana (PETRONAS Research Sdn. Bhd.) | M Amin, Sharidah (PETRONAS Research Sdn. Bhd.)
This paper presents a two-way coupled modelling approach to simulate CO2 movement and containment with geochemical reactions and geomechanical effects. CO2 storage simulation studies cover three main disciplines, reservoir engineering, geochemistry and geomechanics. This new approach of coupled modelling simulation, by simultaneously simulate both effects of geochemistry and geomechanics, is considered as a more representative and better predictive modelling practice.
The integration of geochemistry and geomechanics effects is important for CO2 sequestration modelling. There are a number of published studies on coupled modelling for CO2 storage. However, the majority of the studies has only covered dynamic-geomechanics or dynamic-geochemistry interaction, without considering any direct geomechanics-geochemistry interaction in a reservoir condition. It is crucial to understand the integrated effects when injected CO2 dissolves into formation water and interacts with formation rock. Depending on in-situ conditions, the formation water with dissolved CO2 could weak or strengthen the formation stress due to geochemical reactions of formation minerals. Therefore, coupled modelling is needed to ensure the long-term safety of CO2 containment at a CO2 storage site with the interactions among geomechanical, geochemical and dynamic fluid flow, and especially to understand the slow and not experimentally accessible mineral reactions.
In this paper, a high CO2 content gas field in Malaysia with high temperature (150°C) and high pressure (350 bar) has been studied using integrated coupled modelling approach. The simulation input parameters are first investigated and collected from literature and laboratory studies. A two-way coupled modelling simulation with the consideration of geochemistry and geomechanics effects is desirable because it allows the updates of reservoir properties back and forth in every time step. Different CO2 trapping mechanisms, long term fate analysis, subsidence and heaving analysis, and changes of porosity and permeability are investigated. The time frame of simulation studies consists of CO2 injection period (15 years) and post CO2 injection period (500 years).
During the first 15 years of CO2 injection, 95.13% of injected CO2 is structurally trapped, 3.67% of CO2 is soluted in formation water and 1.2% is trapped by mineralization. About 0.041m of heaving is observed at the injection area while about 0.05m of subsidence is observed at the production area. In the investigation of long-term CO2 fate, it is observed that CO2 gas will be trapped between the lighter hydrocarbon gas layer and aquifer due to density difference.
Chen, Xin (BGP) | Wang, Guihai (CNODC) | Wang, Zhaofeng (CNODC) | Liu, Zundou (CNODC) | Liu, Zhaowei (CNODC) | Cui, Yi (CNODC) | Tian, Wenyuan (CNODC) | Wei, Xiaodong (BGP) | Hou, Liugen (BGP) | Yang, Ke (BGP) | Chen, Gang (BGP) | Xia, Yaliang (BGP) | Yan, Xiaohuan (BGP) | Zhang, Zeren (BGP) | Liu, Jingluan (BGP)
To improve the accuracy of permeability prediction, seismic constraint and sedimentary facies has often been adopted in conventional methods. However, it is porosity that both of them constrain, rather than permeability, and different pore structure with different permeability, the accuracy of permeability prediction cannot be radically improved. To address the problem of permeability prediction in carbonate reservoir, new permeability prediction technique workflow were summarized based on pore structure analysis and multi-parameters seismic inversion: division reservoir types based on the pore structure, construction of the rock types identification curve, carry out a rock type inversion and a porosity inversion constrained by seismic impedance respectively, and then get a final permeability prediction volume according to the porosity-permeability relationship and pore structure of core samples. It breaks the bottleneck that is difficult for seismic impedance (continuous variable) to constrain rock type (discrete variable), then constrains pore structure (continuous variable) related to rock type instead, and converts it into rock type using multi-parameters seismic inversion. According to the certification of new wells, this workflow have been applied successfully in carbonate reservoir of H oilfield in Middle East, it not only improves the prediction of rock type in space, but also permeability prediction accuracy.
Chen, Xin (BGP) | Zhang, Suhong (BGP) | Ou, Jin (CNODC) | Ye, Yufeng (CNODC) | Xu, Lei (CNODC) | Ma, Yingze (CNODC) | Wei, Xiaodong (BGP) | Yang, Ke (BGP) | Chen, Gang (BGP) | Zhou, Guofeng (BGP) | Xia, Yaliang (BGP) | Yan, Xiaohuan (BGP) | Zhang, Zeren (BGP) | Liu, Jingluan (BGP) | Zhou, Xiaoming (BGP)
In order to improve the accuracy of reservoir prediction results, the conventional method usually include seismic inversion, and seismic attribute analysis. Due to the limitation of the vertical resolution of seismic data, it is hard to identify the thin reservoir by seismic attributes directly. In order to improve the prediction accuracy of reservoir, this paper show a new reservoir characterization technique based on geological seismic conditioning. The new method mainly includes five steps. The first step is sedimentary facies classification based on the geological seismic analysis, such as core data, thin section analysis, FMI logging, NMR logging and conventional logging. The second step is modern sedimentary model optimization and forward modelling. In order to establish a reasonable sedimentary facies model, a similar barrier island modern sedimentary model was chosen. To understand the geological significance of seismic data, two different dominant frequency were designed for forward modelling based on the sedimentary facies model and petrophysical analysis. The third step is seismic conditioning under the guide of sedimentary facies model forward modelling. The next step is seismic constraint stochastic inversion, and the last step is reservoir characterization and new well confirm. The application of this method in A oilfield shows that the techniques not only improved the identification ability of the reprocessing seismic data, but also improved the prediction accuracy of the reservoir characterization results. This new reservoir characterization technique can integrated multidisplinary information, such as modern sedimentary model, well data and seismic data, to establish a reasonable sedimentary model, to enhance the resolution of seismic data by conditioning, and get an reasonable reservoir characterization results based on the seismic inversion.
Han, Rubing (Research Institute of Petroleum Exploration and Development, Petrochina) | Li, Shunming (Research Institute of Petroleum Exploration and Development, Petrochina) | Song, Benbiao (Research Institute of Petroleum Exploration and Development, Petrochina) | Tian, Changbing (Research Institute of Petroleum Exploration and Development, Petrochina)
The giant H oil field was discovered in 1976 and put into development in 2008. The Mishrif reservoir has half of the geological reserves, and the current development challenges are greater. First, the sedimentary evolution is very complicated (inner ramp, lagoon, shallow sea, et al), the existing facies model is generally derived from rock type interpolation with kriging algorithm, and does not reflect sedimentary understanding, and is quite different from the actual situation displayed by seismic data. Furthermore, the variogram of rock types is also difficult to be accurate, resulting in poor fitting of reservoir simulation. Second, the seismic data quality is generally low, and its correlation with rock types is worse. If it is directly used to constrain rock type interpolation, the accuracy is generally unsatisfactory.
In order to solve these problems, this study first comprehensively studied the core, thin slices, scanning electron microscopy, X-ray diffraction, electron probe and other data for sequence stratigraphy and sedimentary research. Secondly, based on the single well facies interpretation, combined with the inversion data, the dimension, spatial relationship and variogram of each depositional element were studied. Thirdly, the facies model was built using the Sequential Indicator Simulation (SIS) algorithm, and was manually modified zone by zone according to the sequence stratigraphy and sedimentary understanding. Finally, the relationship between depositional elements and rock types was studied, and the probability bodies of different depositional elements with different rock types were obtained. Based on this, the SIS algorithm was used to simulate rock types. Then this could be further used as a constraint to build petrophysical models.
The results showed that the correlation between the depositional elements and the rock type was obviously better than the inversion wave impedance. The artificially modified facies model could better reflect sedimentary appearance, and various static and dynamic data. The rock type model obtained under the constraint of the facies model also bypassed the problem that the seismic data quality was not good enough for direct rock type interpolation.
It was verified that with the new modeling workflow, the preliminary numerical simulation fitting rate reach over 80%. The facies model was then verified with water flooding test in H oil field and had good results. This workflow could provide a good reference for similar oilfields in the Middle East.
This paper discusses KSI project which is the first in-house study on QA Cluster, aimed to accelerate delivery. This abstract spotlights the surface & subsurface integrated work results on fast track from DG1 to FID within 1.5 years by utilizing data from analogue fields & replication of surface concept & facility design.
For the subsurface, an extensive analogue study was conducted. Then simple 1D analytical model used to generate well by well forecast. A small box model constructed to test different water flood development sensitivity & define the optimum spacing, type of pattern & water injection depth where the outcome compared with 3D simulation model & they match.
For the surface, a small Well Test Unit (WTU) is leased to maximize the oil production from KSI field & provide an early view of reservoir waterflood uncertainty. The full field surface facility concept is a replication from H analogue field. This replication leads to accelerate the on stream date by 24 months.
KSI is a green field which is one of the Lower Shuaiba pancake reservoir where it transferred from exploration with a high UTC project & very long schedule.
It was identified that the key critical success factors are accelerating initial oil production & reducing Capex by using analogue field data, optimized phased-development, replication for facility design, & optimized well design & well spacing.
Comparing the KSI field with analogue fields, resulted on chosen a line-derive waterflood as development concept which was validated by running a box model.
The good match achieved between 1D analytical model used at DG2 & 3D simulation model used at DG3 indicated that the analytical model is sufficient as promise for Field
Development Plan (FDP). However the numerical model will be needed for easily future waterflood management.
Changing the well completion design from single horizontal to dual lateral is resulted in reducing the CAPEX (Drillex) by 54%. The replication of surface facility resulted on achieving two years ahead of initial schedule.
The in-house study & replication of surface facility led to reduce the total project CAPEX 7%, increase NPV by 77%, reduce the project UTC by 21% & accelerated the schedule by 2 years as below
Is Surfactant Environmentally Safe for Offshore Use and Discharge? The current presentation date and time shown is a TENTATIVE schedule. The final/confirm presentation schedule will be notified/available in February 2019. Designing Cement Jobs for Success - Get It Right the First Time! Connected Reservoir Regions Map Created From Time-Lapse Pressure Data Shows Similarity to Other Reservoir Quality Maps in a Heterogeneous Carbonate Reservoir. X. Du, Y. Jin, X. Wu, U. of Houston; Y. Liu, X. Wu, O. Awan, J. Roth, K.C. See, N. Tognini, Shell Intl.
By International Petroleum Technology Conference (IPTC) Monday, 25 March 0900-1600 hours Instructors: Olivier Dubrule and Lukas Mosser, Imperial College London Deep Learning (DL) is already bringing game-changing applications to the petroleum industry, and this is certainly the beginning of an enduring trend. Many petroleum engineers and geoscientists are interested to know more about DL but are not sure where to start. This one-day course aims to provide this introduction. The first half of the course presents the formalism of Logistic Regression, Neural Networks and Convolutional Neural Networks and some of their applications. Much of the standard terminology used in DL applications is also presented. In the afternoon, the online environment associated with DL is discussed, from Python libraries to software repositories, including useful websites and big datasets. The last part of the course is spent discussing the most promising subsurface applications of DL.
Gao, Xiaofei (CNOOC-Shenzhen) | Wu, Yuze (CNOOC-Shenzhen) | Shen, Xu (CNOOC-Shenzhen) | Dai, Ling (CNOOC-Shenzhen) | Chang, Botao (Schlumberger) | Wang, Chao (Schlumberger) | He, Chengwen (Schlumberger)
Development of lithological reservoirs is becoming vital in the Pearl River Mouth basin of the South China Sea. One of these is the Neogene M lithological reservoir in which the deposition of a paleodelta over multiple periods caused a complex profile including severe heterogeneity, rapid lateral property change, poor sand connectivity, and irregular thickness variation (0.5 to 12 m) with interbeds. The current development scope is approaching the predicted eastern sand-pinchout line, making it necessary to identify key points as "golden spikes" to shape the sand bodies’ spatial distribution profile, internal characterization, and pinchout points. based on the sand bodies’ distribution network, drilling and production techniques can be specifically configured to push the development limit as much as possible by efficiently squeezing remaining oil.
In the horizontal well campaign, five appraisal wells are important golden spikes where interwell structural and stratigraphic uncertainties are high due to limited resolution of 3D seismic and sequence stratigraphic data and limited depth-of-investigation (DOI) of conventional logging data. A high-definition deep-looking inversion service was identified to balance resolution and DOI. This novel inversion stochastically analyzes hundreds of formation models using the Metropolis-coupled Markov-chain Monte-Carlo method and then identifies multiple layers (more than three) with 6 m DOI, formation resistivity, anisotropy and dip. With the key resolution-DOI balance, this deep-looking inversion can reveal high-definition interwell details and set a series of golden spikes to identify sand superposition configuration and pinchout points. Within the refined 3D reservoir model, the geo-steering efficiency, completion configuration, and waterflooding stimulation efficiency could be optimized for maximum recovery. Furthermore, a reasonable well pattern arrangement could be developed to sweep the predicted remaining oil and progressively push the development limit.
As evident from ten horizontal wells, high-definition interwell reservoir details were revealed by describing up to four boundaries and five layers simultaneously within maximum 5-m distance from borehole. The golden spikes characterized sand bodies’ profile and their pinchout points. Compared to the prognosis, the southeast margin has been moved to the west. Smooth trajectories were proactively steered to chase irregular sand bodies with minimal loss. Based on the refined 3D reservoir model, proper completion configurations were designed to accommodate the variable properties in this reservoir. One horizontal water-injection well focused on specific discontinuous sand bodies for an average 1.6MPa (megapascal) /well pressure recovery and total 126,000 barrels/year incremental oil. Oil recovery reached 13% within 3.5 years of production, faster than the prognosis. Under current development led by this integrated service, four wells were planned towards updated eastern pinchout line to exploit the remaining oil as much as possible. With increasing distance from the platform, laterals can be placed accurately to achieve objectives with high drilling efficiency and less drilling risk by minimizing unnecessary trajectory adjustments.
From resolution-DOI balance to the identification of golden spikes, this deep-looking inversion could constrain 3D seismic and sequence stratigraphic interpretation to refine the large-scale reservoir model. Considering drilling and production methods, this integrated service could effectively push the development to the potential limit.
Operators are collecting abundant produced-water data that are often underused. Produced-water-composition data provide clues related to the geochemical reactions that are occurring in the subsurface. This information can be useful for monitoring interwell connectivity and predicting and managing oilfield scale resulting from brine supersaturation. Coupling thermodynamic calculations with produced-water analysis helps to identify geochemical effects that could affect oil recovery.
This work addresses the difference that reservoir temperature has on geochemical reactions in carbonate reservoirs by comparing data from two offshore fields and identifying the rock/brine and brine/brine reactions that will affect scale management.
Two seawater-flooded chalk fields located near each other were selected as candidates for comparison. The temperature of one field is 130°C, whereas for the other field, it is 90°C. Produced-water samples (a total of 6,800) from these two fields were analyzed, and the compositional trends were plotted to identify the deviation from conservative (nonreacting) behavior. The compositional trends were then grouped to identify if there were common features between wells. This analysis was complemented by 1D reactive-transport modeling to identify the reactions that would be consistent with the observed trends.
Two groups of wells were identified within each reservoir on the basis of the produced-brine compositional behavior. Each well group exhibits a distinct ion-trend behavior, especially with respect to barium, calcium, strontium, and magnesium concentrations—because these are divalent cations that are abundant in the formation brines. The breakthrough of sulfate, a component primarily introduced during seawater flooding, varies very significantly between the two groups in each case. In one grouping, the sulfate is barely retarded, and it breaks through at seawater fractions lower than 10%. In the other grouping, however, sulfate does not break through until the seawater fraction in the produced brine exceeds 75%. This retardation of sulfate occurs most strongly in the hotter reservoir, and this might be attributed to the lower solubility of the calcium sulfate mineral anhydrite at a higher temperature. The retardation of sulfate then means that barium is produced at higher concentrations because barite precipitation in the reservoir is thus restricted, caused by sulfate being the limiting ion. However, some sulfate stripping does occur in the cooler reservoir, despite the higher solubility of anhydrite. Furthermore, in all cases, magnesium is retarded, with some groupings exhibiting the complete stripping of magnesium from the injected seawater.
The magnesium-stripping behavior is reproduced in the reactive-transport models when calcium- and magnesium-replacement reactions are allowed. This phenomenon has been observed elsewhere in coreflood experiments, and it also contributes to the sulfate stripping through the promotion of anhydrite precipitation within the rock. This process, which is beneficial in terms of reducing the scale risk, is more pronounced at higher temperatures. Therefore, higher-temperature chalk reservoirs might act as natural sulfate-reduction plants, reducing scaling, souring risks and, thus, operating costs of the fields.