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Introduction This chapter is organized to help perform acidizing on a well candidate in a logical step-by-step process and then select and execute an appropriate chemical treatment for the oil/gas well. The guidelines are practical in intent and avoid the more complicated acid reaction chemistries, although such investigations and the use of geochemical models are recommended for more complicated formations or reservoir conditions. Effective acidizing is guided by practical limits in volumes and types of acid and procedures so as to achieve an optimum removal of the formation damage around the wellbore. Most of this chapter is an outgrowth of field case studies and of concepts derived from experimental testing and research. Justification for the practices and recommendations proposed herein are contained in the referenced documents. The reader is referred to the author's previous papers on matrix acidizing for references published before 1990. Concepts and techniques presented have ...
Summary As part of studying miscible gas injection (GI) in a major field within the Green Canyon protraction area in the Gulf of Mexico (GOM), asphaltene-formation risk was identified as a key factor affecting a potential GI project. The industry has not conducted many experiments to quantify the effect of asphaltenes on reservoir and well performance under GI conditions. In this paper we discuss a novel laboratory test for evaluating the asphaltene effect on permeability. The goals of the study were to define the asphaltene-precipitation envelope using blends of reservoir fluid and injection gas, and measure permeability reduction caused by asphaltene precipitation in a core under GI. To properly analyze the effect of GI, a suite of fluid-characterization studies was conducted, including restored-oil samples, compositional analysis, constant composition expansion (CCE), and differential vaporization. Miscibility conditions were defined through slimtube-displacement tests. Gas solubility was determined through swelling tests complemented by asphaltene-onset-pressure (AOP) testing. The unique procedure was developed to estimate the effect of asphaltene deposition on core permeability. The 1-ft-long core was saturated with the live-oil and GI mixture at a pressure greater than the AOP, and then pressure was depleted to a pressure slightly greater than the bubblepoint. Several cycles of charging and depletion were conducted to mimic continuous flow of oil along the path of injected gas and thereby to observe the accumulation of asphaltene on the rock surface. The test results indicated that during this cyclic asphaltene-deposition process, the core permeability to the live mixture decreased in the first few cycles but appeared to stabilize after Cycle 5. The deposited asphaltenes were analyzed further through environmental scanning electron microscopy (ESEM), and their deposition was confirmed by mass balance before and after the tests. Finally, a relationship was established between permeability reduction and asphaltene precipitation. The results from the asphaltene-deposition experiment show that for the sample, fluids, and conditions used, permeability is impaired as asphaltene flocculates and begins to coat the grain surfaces. This impairment reaches a plateau at approximately 40% of the initial permeability. Distribution of asphaltene along the core was measured at the end by segmenting the core and conducting solvent extraction on each segment. Our recommendation is numerical modeling of these test results and using this model to forecast the magnitude of the permeability impairment in a reservoir setting during miscible GI.
Safari, Alireza R. (Mehran Engineering and Well Services Company) | Panjalizadeh, Hamed (Mehran Engineering and Well Services Company) | Pournik, Maysam (University of Texas Rio Grande Valley) | Jafari, Hamed (Mehran Engineering and Well Services Company) | Zangeneh, Alireza (Mehran Engineering and Well Services Company)
Summary The accomplishment of matrix stimulation in highly contrasted permeability reservoirs is critically dependent on diversion. Consequently, assessment of the diversion performance is a key to determine the success of stimulation. However, there are still doubts on the evaluation of diversion effectiveness, especially in long‐interval heterogeneous reservoirs. When a diverter enters the formation, a hump in the surface pressure curve is usually expected. Then, it can be interpreted as supporting evidence for diversion. However, this is a simplification of the fluid‐diversion process. It could be possible that a hump is not observed during a diversion stage, although it is effective. Therefore, what should be done? To overcome this challenge, we propose a more‐accurate diversion‐evaluation method and validate it with available matrix‐stimulation data. Three methods were introduced in the literature to evaluate matrix‐stimulation performance: Paccaloni, Prouvost, and Chan [inverse injectivity (i.e., Iinv)] methods (Prouvost and Economides 1987, 1989; Paccaloni and Tambini 1993; Chan et al. 2003). The latter is easy to use and accurate, which accounts for transient flow effects. In this paper, the inverse injectivity method is modified and validated with the real data of two matrix‐acidizing operations in a gas/condensate field. The performed modifications in the evaluation process include a bottomhole‐pressure‐calculation procedure, which is validated with available drillstem‐test (DST) matrix‐stimulation data, and simultaneous utilization of Iinv and its derivative plot. Humps in the Iinv plot, which can be interpreted as diverter performance, are sometimes so small that it is difficult to distinguish the diverter effect from possible noises in the data. Here, the derivative plot of Iinv is used as a complementary tool to improve the interpretation process. Results indicate that for both wells in this study, the modified Iinv shows clear humps when diverters enter the reservoir. In addition, exactly when Iinv builds up, a sign change in the derivative plot is observed. This shows that these two parameters have a confirming behavior. Finally, pre/post‐stimulation production data were used to practically prove the calculations behind the method. Here, the target of design was to divert stimulation fluids to the low‐permeability bottom layer because it was both a high-pressure and high-hydrocarbon reserve. Per production‐logging data, the majority of production before stimulation was originated from a sublayer. In the first operation, with the rare appearance of surface pressure humps, Iinv and its derivative showed satisfactory outputs of diversion occurrence. After stimulation, production logging confirmed the diversion of flow and nearly uniform production across the targeted interval. Hence, this indicates that the modified method accurately demonstrates the performance of the diversion system in acidizing operations with long perforated intervals, even if there is a rare distinct pressure hump in the surface. Therefore, this could be adapted either for cases where there is no access to the production logging or for the cases in which the hump in surface pressure is not observed.
Summary The analysis of gas production from fractured ultralow-permeability (ULP) reservoirs is most often accomplished using numerical simulation, which requires large 3D grids, many inputs, and typically long execution times. We propose a new hybrid analytical/numerical method that reduces the 3D equation of gas flow into either a simple ordinary-differential equation (ODE) in time or a 1D partial-differential equation (PDE) in space and time without compromising the strong nonlinearity of the gas-flow relation, thus vastly decreasing the size of the simulation problem and the execution time. We first expand the concept of pseudopressure of Al-Hussainy et al. (1966) to account for the pressure dependence of permeability and Klinkenberg effects, and we also expand the corresponding gas-flow equation to account for Langmuir sorption. In the proposed hybrid partial transformational decomposition method (TDM) (PTDM), successive finite cosine transforms (FCTs) are applied to the expanded, pseudopressure-based 3D diffusivity equation of gas flow, leading to the elimination of the corresponding physical dimensions. For production under a constant- or time-variable rate (q) regime, three levels of FCTs yield a first-order ODE in time. For production under a constant- or time-variable pressure (pwf) regime, two levels of FCTs lead to a 1D second-order PDE in space and time. The fully implicit numerical solutions for the FCT-based equations in the multitransformed spaces are inverted, providing solutions that are analytical in 2D or 3D and account for the nonlinearity of gas flow. The PTDM solution was coded in a FORTRAN95 program that used the Laplace-transform (LT) analytical solution for the q-problem and a finite-difference method for the pwf problem in their respective multitransformed spaces. Using a 3D stencil (the minimum repeatable element in the horizontal well and hydraulically fractured system), solutions over an extended production time and a substantial pressure drop were obtained for a range of isotropic and anisotropic matrix and fracture properties, constant and time-variableQ and pwf production schemes, combinations of stimulated-reservoir-volume (SRV) and non-SRV subdomains, sorbing and nonsorbing gases of different compositions and at different temperatures, Klinkenberg effects, and the dependence of matrix permeability on porosity. The limits of applicability of PTDM were also explored. The results were compared with the numerical solutions from a widely used, fully implicit 3D simulator that involved a finely discretized (high-definition) 3D domain involving 220,000 elements and show that the PTDM solutions can provide accurate results for long times for large well drawdowns even under challenging conditions. Of the two versions of PTDM, the PTD-1D was by far the better option and its solutions were shown to be in very good agreement with the full numerical solutions, while requiring a fraction of the memory and orders-of-magnitude lower execution times because these solutions require discretization of only the time domain and a single axis (instead of three). The PTD-0D method was slower than PTD-1D (but still much faster than the numerical solution), and although its solutions were accurate for t < 6 months, these solutions deteriorated beyond that point. The PTDM is an entirely new approach to the analysis of gas flow in hydraulically fractured ULP reservoirs. The PTDM solutions preserve the strong nonlinearity of the gas-flow equation and are analytical in 2D or 3D. This being a semianalytical approach, it needs very limited input data and requires computer storage and computational times that are orders-of-magnitude smaller than those in conventional (numerical) simulators because its discretization is limited to time and (possibly) a single spatial dimension.
Rachapudi, R. V. (ADNOC Onshore) | Al-Jaberi, S. S. (ADNOC) | Al Hashemi, M. (ADNOC) | Punnapala, S. (ADNOC Onshore) | Alshehhi, S. S. (ADNOC Onshore) | Talib, N. (ADNOC Onshore) | Loayza, A. F. Jimenez (ADNOC Onshore) | Al Nuimi, S. (ADNOC Onshore) | Elbekshi, A. (ADNOC Onshore) | Quintero, F. (ADNOC Onshore) | Yuliyanto, T. (ADNOC Onshore) | Abd Rashid, A. Bin (ADNOC Onshore) | Alkatheeri, F. Omar (ADNOC Onshore) | Gutierrez, Daniel (ADNOC Onshore) | Chehabi, W. (Fishbone A/S) | Hussain, Ali Ba (ADNOC Onshore)
Productivity enhancement of tight carbonate reservoirs (permeability 1-3 md) is critical to deliver the mandated production and to achieve the overall recovery. However, productivity improvement with conventional acid stimulation is very limited and short-lived. Tight reservoirs development with down spacing and higher number of infill wells can increase the oil recovery. Nevertheless, poor vertical communication (Kv/Kh < 0.5) within the layered reservoir is still a challenge for productivity enhancement and needs to be improved.
First time successful installation of fishbone stimulation technology at ADNOC Onshore targeted establishing vertical communication between layers, in addition to maximizing the reservoir contact. Furthermore this advanced stimulation technology connects the natural fractures within the reservoir, bypasses near well bore damage and allows the thin sub layers to produce. This technology requires running standard lower completion tubing with Fishbone subs preloaded with 40ft needles, and stimulation with rig on site. This paper presents the case study of the fishbone stimulation technology implemented at one of the tight-layered carbonate reservoir.
A new development well from ADNOC Onshore South East field was selected for implementation of this technology. The well completion consisting of 4 ½ liner with 40 fishbone subs was installed, each sub containing four needles at 90 degrees phasing capable of penetrating the reservoir up to 40 ft. While rig on site, acid job was conducted for creating jetting effect to penetrate the needles into the formation. Upon completion of jetting operation, fishbone basket run cleaned the unpenetrated needles present in the liner to establish the accessibility up to the total depth. Overall, application of this technology improved the well production rate to 1600 BOPD compared to 400 BOPD of production from nearby wells in the same PAD and reservoir. In addition the productivity of the candidate well improved by 2.5 times with respect to near-by wells in the same PAD. Currently, long-term sustainability testing preparation is in progress. This paper provides the details of candidate selection, completion design, technology limitations, operational challenges, post job testing and lessons learned during pilot implementation. In summary, successful application of this technology is a game changer for tight carbonate productivity enhancement that improves the overall recovery along with optimizing the drilling requirements. Currently, preparation for implementation of 10 pilots in one of the asset at ADNOC Onshore fields is in progress.
Soni, Kishan (Petroleum Affairs Division, Department of Communications, Climate Action and Environment, Ireland/ iCRAG, School of Earth Sciences, University College Dublin) | Manzocchi, Tom (iCRAG, School of Earth Sciences, University College Dublin) | Haughton, Peter (iCRAG, School of Earth Sciences, University College Dublin) | Carneiro, Marcus (iCRAG, School of Earth Sciences, University College Dublin)
Oil reservoirs hosted in deep-water slope channel deposits are a challenge to manage and model. A six-level hierarchical arrangement of depositional elements within slope channel deposits has been widely recognized, and dimensional (width and thickness) and stacking (amalgamation ratio and volume fraction) data have been acquired from published studies to establish parameters for a representative slope channel system. A new static modelling workflow has been developed for building models of channel complexes based on a simplified hierarchical scheme using industry-standard object-based modelling methods and a new plugin applying the compression algorithm. Object-based modelling using the compression algorithm allows for independent input of volume fractions and amalgamation ratios for channel and sheet objects within a hierarchical modelling workflow. A base-case channel complex model is built at the resolution of individual sandstone beds, conditioned to representative dimensional and stacking characteristics of natural systems. Inclusion of explicit channel axis and margin regions within the channels governs bed placement and controls inter-channel connectivity where channels are amalgamated. The distribution of porosity and permeability within these beds mimics grain-size trends of fining in the vertical and lateral directions. The influence of various geological parameters and modelling choices on reservoir performance have been assessed through water-flood flow simulation modelling. Omission of the compression method in the modelling workflow results in a three-fold increase in oil recovery at water-breakthrough, because the resultant unnaturally high amalgamation ratios result in overly-connected flow units at all hierarchical levels. Omission in the modelling of either the bed-scale hierarchical level, or of the axial and marginal constraints on the bed placement in models that do include this level, results in a two-fold increase in oil recovery at water-breakthrough relative to the base-case, because in these cases the channel-channel connections are too permissive.
After long-time water injection, thief zones (TZ) tend to form and reduce the effectiveness of water flooding in mature oil fields. Several profile control techniques have been developed to resolve this problem. The effect of profile control depends on quantitative calculation of pore-throat size and volume of the thief zones which determines the most critical treatment factors such as the injection particle size and slug volume. Tracer tests or ‘PI’ index were normally used to identify thief zones. However, tracer tests are time-consuming and high-cost, especially for offshore fields; ‘PI’ index only reveals a relatively higher permeability area but not necessarily indicate presence of thief zones.
This paper presents a new method to identify TZ as well as pore-throat sizes and volumes calculation by using the variation and derivative of water cut. The procedures are as following:
Two theoretical models of injection and production were established to simulate water flooding development by stream tube method. The first model is a standard model and includes only normal reservoirs. The second model is a comparison model with presence of both high permeability zones and normal permeability zones. The water cut of two models was compared to distinguish the key points and curve features of TZ models. The key points and derivative curve were used to identify the existence of TZ. The ratio of high permeability zones to normal permeability zones as well as the absolute permeability, width and height of TZ were figured out using the peak values and their arrival times on the derivative curve of water cut. Calculate pore-throat radius and porosity of TZ using the absolute permeability in step 3 based on mercury injection capillary pressure (MICP) and then the pore volume of the TZ was determined.
Two theoretical models of injection and production were established to simulate water flooding development by stream tube method. The first model is a standard model and includes only normal reservoirs. The second model is a comparison model with presence of both high permeability zones and normal permeability zones.
The water cut of two models was compared to distinguish the key points and curve features of TZ models. The key points and derivative curve were used to identify the existence of TZ.
The ratio of high permeability zones to normal permeability zones as well as the absolute permeability, width and height of TZ were figured out using the peak values and their arrival times on the derivative curve of water cut.
Calculate pore-throat radius and porosity of TZ using the absolute permeability in step 3 based on mercury injection capillary pressure (MICP) and then the pore volume of the TZ was determined.
In a word, the fluctuation of the water cut curve and the multi-peak values of the water cut derivative curve are due to the fact that the injected water first reaches the production well along the high permeability layer of TZ, and then reaches the production well along the normal reservoir. Furthermore, larger pore volume of TZ will have more influence on water cut value and a larger water cut will be seen when the second peak value occurs on water cut derivative curve.
This workflow had been applied to QHD32-6 oilfield for the profile control treatment design of over 10 well-groups were planned and achieved commendable results: the maximum water cut reduction reached 8% and the oil production noticeable increased by 300bbls per day with an output ratio over 5:1.
Well productivity reduction over time is one of the critical issues for deep-water wells with huge implications on expected recoveries from these wells. It is important to account for this uncertainty accurately in order to generate reliable production forecasts. Typically, reservoir simulation engineers utilize an expression (e.g. linear or exponential) for modeling changes in skin or Productivity Index (PI) over time as a function of either time or cumulative liquid production or pressure depletion. These commonly used single variable-based PI degradation modeling methods are easy to implement with a flow simulator, but they do not address the multi-dimensional nature of PI degradation which is a result of multiple subsurface effects combined with operational conditions. As a result, these single variable-based modeling methods generally do not have good reliability for predicting PI degradation trend.
This article proposes a method for predicting reduction in producing well's PI by integrating a few key well operating variables (drawdown, borehole depletion, and water cut) into a single mathematical formulation. One of the important assumptions of IPDM is that certain critical drawdown pressure exists for each well in the field. When a well is operated below the critical drawdown pressure, negligible to no PI reduction is observed; however, when drawdown exceeds the critical drawdown value, noticeable PI reduction is seen. The reduction level depends on the ratio of current drawdown pressure to critical drawdown pressure, as well as on pressure depletion and water cut levels. By doing so, the global trend and local granularity of PI reduction are well captured. The concept of critical drawdown used in IPDM is aligned well with the awareness of safe drawdown among Reservoir Management practitioners. Critical drawdown ranges derived from IPDM form a useful analog data set while deciding safe drawdown limits or forecasting PI degradation trends for future wells.
The predictability and generality of IPDM were assessed with historical well test (or PTA – Pressure Transient Analysis) data from more than 50 wells across seven deep-water fields. A detailed workflow of implementing IPDM was demonstrated through one of the field applications. From practical implementation point of view, IPDM method can be easily written in Excel Macro or using a PYTHON script or any other programming language. Once the methodology is coded (or implemented), it can then be plugged in a dynamic flow simulator (e.g. INTERSECT™). A similar approach is usually taken while incorporating single variable-based method for forecasting PI degradation into a flow simulator. Compared to the coupled modeling of geo-mechanical simulator - dynamic flow simulator, the IPDM is a much simpler approach to use and also enables engineers to evaluate the impact of key operating conditions on individual well's PI.
Time-lapse (4D) seismic is an essential tool for monitoring the subsurface in and around producing hydrocarbon or CO2 storage reservoirs. The seismic time-shifts, in the reservoir as well as in the overburden, depend on the stress changes and strains induced by the subsurface depletion or the inflation. In this study, geomechanical modeling is used to quantify the stress changes and strains in a synthetic model for the formations in and around a depleting reservoir. The estimated strains are coupled to experimentally determined strain sensitivities for P-wave velocities of shales, to predict time-shifts in the surroundings of the reservoir. The modeling shows that the stiffness contrast between the reservoir and its surroundings plays an important role in controlling the stress and strain changes in the subsurface. The strain sensitivity of the vertical P-wave velocity in the surroundings is significant and is rapidly increasing in magnitude with the proximity to the reservoir. Correspondingly, the time-shifts are increasing with depth in the overburden and decreasing with depth in the underburden. In this study, the time-shifts of the surroundings are changing most between the depths corresponding to one and two reservoir radii above and below the reservoir. Presentation Date: Wednesday, October 14, 2020 Session Start Time: 8:30 AM Presentation Time: 11:00 AM Location: 360A Presentation Type: Oral