As an enhanced oil recovery method (EOR), chemical flooding has been implemented intensively for some years. Low Salinity WaterFlooding (LSWF) is a method that has become increasingly attractive. The prediction of reservoir behaviour can be made through numerical simulations and greatly helps with field management decisions. Simulations can be costly to run however and also incur numerical errors. Historically, analytical solutions were developed for the flow equations for waterflooding conditions, particularly for non-communicating strata. These have not yet been extended to chemical flooding which we do here, particularly for LSWF. Dispersion effects within layers also affect these solutions and we include these in this work.
Using fractional flow theory, we derive a mathematical solution to the flow equations for a set of layers to predict fluid flow and solute transport. Analytical solutions tell us the location of the lead (formation) waterfront in each layer. Previously, we developed a correction to this to include the effects of numerical and physical dispersion, based on one dimensional models. We used a similar correction to predict the location of the second waterfront in each layer which is induced by the chemical's effect on mobility. In this work we show that in multiple non-communicating layers, material balance can be used to deduce the inter-layer relationships of the various fronts that form. This is based on similar analysis developed for waterflooding although the calculations are more complex because of the development of multiple fronts.
The result is a predictive tool that we compare to numerical simulations and the precision is very good. Layers with contrasting petrophysical properties and wettability are considered. We also investigate the relationship between the fractional flow, effective salinity range, salinity dispersion and salinity retardation.
This work allows us to predict fluids and solute behaviour in reservoirs with non-communicating strata without running a simulator. The recovery factor and vertical sweeping efficiency are also very predictable. This helps us to upscale LSWF by deriving pseudo relative permeability based on our extension of fractional flow and solute transport into such 2D systems.
Application of polymer flooding as a chemical Enhanced Oil Recovery (EOR) has increased over recent years. The main type of polymer used is partially hydrolyzed polyacrylamide (HPAM). This polymer still has some challenges especially with shear stability and injectivity that restrict its utility, particularly for low permeability reservoirs. Injectivity limits the possible gain by acceleration in oil production due to polymer flooding. Hence, good polymer injectivity is a requirement for the success of the operation. This paper aims to investigate the influence of formation permeability on polymer flow in porous media.
In this study, a combination of core flooding with rheological studies is presented to evaluate the influence of permeability on polymer in-situ rheology behavior. The in-situ flow of HPAM polymers has also been studied for different molecular weights. The effect of polymer preconditioning prior to injection was studied through exposing polymer solutions to different extent of mechanical degradation.
Results from this study reveal that the expected shear thinning behavior of HPAM that is observed in rheometer measurements is not observed in in-situ rheology in porous media. Instead, HPAM in porous media exhibits near-Newtonian behavior at low flow rates representative of velocities deep in the reservoir, while exhibiting shear thickening behavior at high flow rates representative of velocities near wellbore region. The pressure build-up associated with shear thickening behavior during polymer injection is significantly higher than pressure differential during water injection. The extent of shear thickening is high during the injection of high Mw polymer regardless of cores' permeability. In low permeable Berea cores, shear thickening and mechanical degradation occur at lower velocities although the degree of shear thickening is lower in Berea to that observed in high permeable Bentheimer cores. This is ascribed to high polymer retention in Berea cores that results in high residual resistance factor (RRF). Results show that preshearing polymer before injection into porous media optimizes its injectability and transportability through porous media. The effect of preshearing becomes favorable for the injection of high Mw polymers into low permeability formation.
This study discusses polymer in-situ rheology and injectivity, which is a key issue in the design of polymer flood projects. The results provide beneficial information on optimizing polymer injectivity, in particular, for low permeability porous media.
The field-scale design of chemical enhanced oil recovery (cEOR) processes requires running complex numerical models that are computationally demanding. This paper provides an efficient screening platform for the cEOR feasibility study by presenting five artificial neural network (ANN) based models. We constructed 1,100 ANN training cases using CMG-STARS to capture the variation in reservoir petrophysical properties and the range of injected chemicals properties for a five-spot pattern. The design parameters were coupled with the reservoir properties using several functional links to optimize the ANN models and improve their performances. The training cases were employed using back-propagation methods to construct one forward model (Model #1) and four inverse models. Model #1 predicts reservoir response (i.e., oil rate, water cut, injector bottomhole pressure, cumulative oil) for known reservoir characteristics (i.e., permeability, thickness, residual oil saturation, chemical adsorption) and project design parameters (i.e., pattern size, chemical slug size and concentration), Model #2 predicts reservoir characteristics by history matching the reservoir response, and Model #3 predicts project design parameters for known reservoir response and characteristics. Models #4 and #5 predict project design parameters for a targeted cumulative oil volume and project duration time, which is useful for economical evaluation before the implementation of cEOR projects.
The validation results show that the developed ANN-based models closely predict the numerical results. In addition, the models are able to reduce the computational time by four orders of magnitude, which is significant considering the complexity of cEOR modeling and the need for reliable and efficient tools in building cEOR feasibility studies. In terms of accuracy, Model #1 has a prediction error of 5% whereas the error for other four inverse ANN models is about 20–40%. To enhance the performance of the inverse ANN models, we changed the ANN structure, increased training cases, and used functional links, which slightly reduced the error. Further, we introduced a back-check loop that uses the predicted parameters from the inverse ANN models as inputs in the forward ANN model. A comparison of back-check results for the reservoir response with the numerical results delivers a relatively small error of 10%, revealing the non-uniqueness of solutions obtained from the inverse ANN models.
Fractures can be first-order controls on fluid flow in hydrocarbon reservoirs. Understanding the characteristics of fractures such as their aperture, density, distribution, conductivity, connectivity, etc, is key for reservoir engineering and production analysis.
Well testing plays a key role in the the characterisation of fractured reservoirs, especially. New advances in the Pressure Transient Analysis (PTA) have enabled the interpretation of production data in a way where the resulting geological scenarios are in better agreement with fracture patterns observed in outcrop analogues.
Traditionally, Drill Stem Test (DST) data have been the primay source of information for well testing. However, we hypothesise that wireline conveyed tools designed for Interval Pressure Transient Testing (IPTT) could yield a more throrough description of the near-wellbore heterogeneities, including fractures.
Hence, we investigate the applicability of IPTT for characterising fractured reservoirs using detailed numerical simulations models with accurate wellbore representation to generate synthetic IPTT responses that can obtained through a next-generation wireline testing tool called SATURN. We particularly focus on cases where fractures are present in the near-wellbore region but do not intersect the wellbore. The study included parameters such as fracture densities and conductivities, distance between fractures and wellbore and the vertical extension of the fractures across geological beds.
The impact of the different fracture scenarios on the pressure transient tests was recorded as characteristic signatures on diagnostic plots (pressure derivative curves). We have called these curves "IPTT-Geotypes"; they can be used to assist the interpretation process of IPTT responses. To the best of our knowledge, this is the first time pressure derivative type curves for IPTT in fractured reservoirs are presented in the literature.
A field example of an IPTT case was analysed using the concept of geological well testing. We integrated the information from petrophysical logs and the IPTT-Geotypes to assist the calibration of a reservoir model developed to represent the geological setting of the tested reservoir interval. The results provided a sound interpretation of the reservoir geology and quantitative estimation of the matrix and fracture parameters.
Presence of H2S detected in producing wells of North Kuwait sweet waterflooded reservoirs over the last 18 years, gave indications of biogenic souring. In response to this, the Kuwait Oil Company engaged in detailed souring potential assessments of selected reservoirs such as the Raudhatain Mauddud (RAMA), to predict the further generation of H2S and define the required souring mitigation strategy to ensure safe production over the remaining field life.
The souring simulation modelling was conducted on the RAMA subsurface model with support from Shell, using a state of the art souring prediction program. The initial phase of the study consisted in the history match simulation to define the most likely souring mechanism in the field. The forecast considered various scenarios with a range of sensitivities on carbon nutrient and sulphate levels, both in formation and injected water in the field.
The history match simulation results showed a good correlation with most of the producers with available H2S data. The Forecast simulation over the next 15-year period predicts a moderate souring severity for this reservoir, based on the maximum H2S mass flow rate of 90 kg/d and H2S in gas maximum concentration of 85 ppmv at the field level.
This work provides the petroleum Industry further insights into the souring behavior when effluent water is injected in addition to seawater, particularly the effects of additional carbon nutrients fed into the reservoir.
The objective of this work is to characterize the fault system and its impact on Mishrif reservoir capacity in the West Quran oil field. Determination and modelling of these faults are crucial to evaluate and understanding fluid flow of both oil and water injection in terms of distribution and the movement. In addition to define the structure away from the well control and understanding the evolution of West Qurna arch over geologic time.
In order to achieve the aim of the work and the structural analysis, a step wise approach was undertaken. Primarily, intensive seismic interpretation and building of structure maps were carried out across the high resolution of 3D-seismic survey with focusing on the main producing Mishrif reservoir of the field. Also, seismic attributes volumes provided a good information about the distribution and geometry of faults in Mishrif reservoir. The next step, it constructs 3-D fault model which will be later merged into the developed 3D geological model. West Qurna/1 oil field situated within the Zubair Subzone, and it is structurally a part of large anticline towards the north. The observation of seismically derived faults near Mishrif reservoir indicated en-echelon faults which refer to strike-slip tectonics along with extensional faults. The statistic of Mishrif interval faulting indicates a big number faults striking north-south along western wedge of anticline. The seismic interpretation, in combination with seismic attributes volumes, deliver a valuable structural framework which in turns used to build a better geological model.
In this paper, the work demonstrates a better understanding for the perspectives on the seismic characterization of the structural framework in the Mishrif reservoir, and also for similar heterogeneous carbonate reservoirs. Further, this work will ultimately lead to improve reservoir management practises in terms of production performance and water flooding plan.
Tamar is a high permeability clastic gas reservoir that behaves like a well-connected tank, in many respects. At the same time, it has a significant level of complexity. The reservoir is comprised of three sand intervals, which are separated vertically by shales and broken into a number of fault blocks. While the degree of aquifer support has been an uncertainty, it is believed that the field demonstrates components of both bottom water and edge water drive. All Tamar wells were equipped with permanent downhole pressure and temperature gauges, and the surveillance of these pressure and rate data over the five-year production history has provided an unusually comprehensive data set.
To date, our feasibility studies [CMTC-502487-MS and SPE-190163-MS] of the Gad and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) process for the South Rumaila oil field have considered using Carbon Dioxide gas injection to enhance recovery from the field. As availibiulity of CO2 is limited and its cost considerable it might be also feasible to use natural gas,, Associated Produced Gas (APG) as an alternative solvent to enhance oil recovery with this process. In the study, efficiency of APG vs. CO2 is compared for the South Rumaila oil field.
In the study, the GDWS-AGD process installation includes 20 vertical APG injection wells are drilled to the top of the reservoir to build a gas cap in the oil pay zone. In addition, eleven horizontal oil-producing wells are placed at the bottom of the oil pay zone with six horizontal water drainage (sink) wells below the oil-water contact (OWC). The two horizontal leg installation may be made from a vertical well with 7-casing dual-completed (from two kick-off points) in the oil payzone and in the bottom water (below OWC) with two horizontal well legs and the two 2-3/8 inch tubings in each well. In a dual-tubing design of the process the two horizontal well legs produce independently. If only one tubing is used production from the water sink well is hydraulically isolated inside the vertical well by a packer. In either design, the water sink well is operated with a submersible pump.
In this study, the GDWS-AGD process with APG is considered for the upper sandstone member/South Rumaila Oil Field, located in Iraq to improve oil recovery. The Rumaila field has an infinite acting-aquifer with very strong edge water drive. In the GDWS-AGD, the bottom water drainage would not only reduce water cut and water cresting, but would also significantly reduce the reservoir pressure, resulting in improving gas injectivity. The study shows considerable improvement with the GDWS-AGD process - oil recovery increased from 76% by CO2 to 83% by APG and water cut was readily controlled resulting in more rapid reduction with APG (from 98% to less than 5%) than that with CO2 in all horizontal oil producers. The results show that the use of APG gas alternative for the GDWS-AGD process not only improves water-cresting control due prompt reduction of water cut, but also enhances gas injectivity and significantly improves oil recovery.
Engineers need to predict the production characteristics from hydraulically fractured wells in tight gas fields. Decline curve analysis (DCA) has been widely used over many years in conventional oil and gas fields. It is often applied to tight gas, but there is uncertainty regarding the period of production data needed for accurate prediction.
In this paper decline curve analysis of simulated production data from models of hydraulically fractured wells is used to to develop improved methods for calibrating decline curve parameters from production data. The well models were constructed using data from the Khazzan field in Oman. The impact of layering, permeability and drainage area on well performance is also investigated. The contribution of each layer to recovery and the mechanisms controlling that contribution is explored.
The investigation shows that increasing the amount of production data used to fit a hyperbolic decline curve does not improve predictions of recovery unless that data comes from many years (20 years for a 1mD reservoir) of production. This is because there is a long period of transient flow in tight gas reservoirs that biases the fitting and results in incorrect predictions of late time performance. Better predictions can be made by estimating the time at which boundary dominated flow is first observed (tb), omitting the preceding transient data and fitting the decline curve to a shorter interval of data starting at tb. For single layer cases, tb can be estimated analytically using the permeability, porosity, compressibility and length scale of the drainage volume associated with the well. Alternatively, tb can be determined from the production data allowing improved prediction of performance from 2-layer reservoirs provided that a) there is high cross-flow or b) there is no cross-flow and the lower permeability layer either does not experience BDF during the field life time or it is established quickly.
Hadi, Farqad (Petroleum Engineering Department, Baghdad University) | Albehadili, Ali (Iraqi Drilling Company) | Jassim, Abduihussein (Najaf Oil Fields) | Almahdawi, Faleh (Petroleum Engineering Department, Baghdad University)
Formulating a prediction tool that can estimate the formation permeability in uncored wells is of particular importance for many applications related to reservoir simulation and production management. Although formation permeability can be obtained from a laboratory or from a reservoir, core analysis and well-test data are limited due to cost and time-saving purposes. A major challenge of previous methods is that they are required other parameters to be previously computed such as porosity and water saturation. In addition, they are affected by the uncertainty that introduced by the cementation factor and saturation exponent. This study presents two prediction methods, multiple regression analysis (MRA) and artificial neural networks (ANNs), to estimate formation permeability using conventional well log data.
The prediction methods were demonstrated by means of a field case in SE Iraq. The study uses core/well log data from Mishrif reservoir which is mainly composed of carbonate (limestone) formations. Two traditional methods were reviewed and presented for permeability determination. These methods are the classical method and the flow zone indicator (FZI) method.
At the same porosity, the results showed a wide range of formation permeability prediction. This result gives a special attention to the assumption that the relationship between permeability and porosity is generally unique in carbonate environments. The deep lateral log resistivity appears to be more conservative in the permeability function rather than other parameters, followed in decreasing order by bulk density, sonic travel time, micro and shallow resistivities, and shale volume. Although the presented models based on RA and ANNs resemble to be closely in determining the formation permeability, the correlation coefficient of ANNs was found to be higher than that obtained from RA, which indicated that the ANNs is more precise than RA. The comparison among previous methods shows the superiority of the FZI method rather than the classical method. However, core porosity and permeability should be previously determined to apply FZI method. This study presents efficient and cost-effective models for a prediction of permeability in uncored wells by incorporating conventional well logs.