Se, Yegor (Chevron U.S.A. Inc) | Galimzhanov, Saken (Tengizchevroil) | Amangaliyev, Bolat (Tengizchevroil) | Aitzhanov, Abzal (Tengizchevroil) | Yechshanov, Ilyas (Tengizchevroil) | Iskakov, Elrad (Chevron U.S.A. Inc) | Ghomian, Yousef (Tengizchevroil) | Bopiyev, Chingiz (Tengizchevroil) | Wang, Haijing (Chevron U.S.A. Inc)
Sour gas injection (SGI) in the non-fracture platform area of the giant carbonate oil field, Tengiz, began in 2007. SGI project was proven to successfully maintain reservoir pressure in the platform area, add significant reserves, reduce sulfur production, and enable additional oil processing capacity at the crude processing facility. Despite the confirmed benefits, the gas breakthrough and increasing gas-oil ratio (GOR) trends in several SGI producers became a concern as the injection project matured. The preferential production from wells with lower GOR allowed higher total oil throughput, but also introduced production constrain on SGI wells with higher GOR. As the result, SGI producers were historically choked back or completely shut-in as soon as the gas breakthrough was confirmed and the producing GOR began to increase above 500m3/m3.
The reservoir heterogeneity with the sour gas injection overprint created complex dynamic environment at the subsurface. Special surveillance program was designed to improve understanding of gas front movement through the reservoir, assess vertical and areal sweep efficiency and remaining oil in place in various zones of interest. Surveillance program design had to overcome several operational constrains, such as wellbore accessibility issues from the scale build, gas handling limits of the surface facilities, and complex simultaneous operations near the active high-pressure sour gas compressor. Moreover, the log interpretation had to consider crossflow and stimulation chemicals impact on the logging measurements. Finally, the integration of logging interpretation results with reservoir model was required to improve the reservoir model forecast and boost the value of acquired information.
This paper describes the results of the conducted surveillance campaign, the novel calibration methodology of gas saturation profile from the time-lapse cased hole measurements with proxy from the multi-component simulation model output and the early results of the performed gas shut-off operations. The described methodology allowed direct calibration of the model outputs with the gas saturation results from pulse neutron logs and provided more accurate sweep efficiency and oil recovery forecast across the entire SGI area. Calibrated model revealed consistent gas breakthrough profile and significant volume of low GOR oil remaining in the wells with gas breakthrough.
The updated reservoir model was then used to evaluate various development scenarios of SGI area. Gas shut-off scenario showed particularly encouraging low GOR production trends and improved oil recovery especially from the lower intervals. After the economic analysis, several wells, including long-term shut-ins, were added to the workover queue to timely realize production benefits. Early production results after gas shut-off workover consistently met or exceeded model forecasts. Described methodology provided more accurate scope definition, value assessment and justification for the SGI optimization project and could be applicable to other improved oil recovery projects.
This paper describes a trial project to evaluate autonomous inflow control device (AICD) technology to better manage water production in a large heavy oil field in Colombia. The Cajua block is part of the Rubiales field is in the Llanos basin of Eastern Colombia, and has reserves estimated at 7.5 billion barrels. One of the main production challenges is the high water cut, or BSW, driven by strong aquifer flow in the underlying sands of the Carbonera formation. Many wells experience early water break-through and must be produced above 95% BSW for long periods of time. Horizontal wells typically produce up to 8000 barrels per day of total fluid with electric submersible pump (ESP) on cold production, and do not utilize any thermal recovery methods. The loosely-consolidated sandstone reservoir has variable water saturation and permeability, which has continuously frustrated operators'’ attempts to manage water production ever since the Rubiales field was first brought online in the 1980's.
In late 2018, a three well pilot project was initiated to evaluate the ability of inflow control technology to manage water influx at the sandface of the horizontal completions. Three wells in the Cajua block were equipped with AICD screens and swellable packers to evaluate oil production and water cut. The AICD technology works by limiting water inflow based on fluid viscosity. Each segment, or compartment, of the horizontal wellbore is isolated by swellable packers, and the AICD creates a higher or lower drawdown on the reservoir depending on the fluid properties, favoring the inflow of high-viscosity heavy oil over the low-viscosity water.
The early production results show that AICD completions can effectively manage water production by delaying water break-through and restricting water inflow from the reservoir. Each of the three trial wells responded positively to the autonomous ICDs, allowing engineers to produce heavy oil wells more effectively with lower cumulative water volumes.
This project marks the first implementation in South America of AICD technology with rate-controlled production (RCP) valves to manage water production in a heavy oil field. It is also the second application worldwide, after Canada, to show that AICDs can effectively to manage water cut in a heavy oil, cold-production scenario.
The traditional definition of volumetric sweep efficiency sums the effects of both fingering (arising due to contrasts in mobility) and bypassing (arising due to contrasts in permeability as well as well placement). Accordingly, we cannot quantitatively attribute poor sweep to either bypassing or fingering. Similarly, in EOR, the incremental recovery cannot be quantitatively associated with the reduction of those effects. For such purposes, we rely on visualization and mapping of saturation profiles to quantify and characterize the remaining oil in place including its distribution. . In this work, we propose a complementary method to obtain an instantaneous insight of the remaining oil distribution. We demonstrate the decomposition of fingering and bypassing effects and its utility. We first redefine recovery factors such that we decouple bypassing and fingering effects. We then validate those redefined sweep indicators by examining a 5-spot waterflood and two idealistic polymer floods. Later, we demonstrate the possible utility of those redefined sweep indicators through different examples. In one example, we compare the performance of a shear - thinning polymer to a recovery-equivalent Newtonian polymer. Using fingering and bypassing sweep indicators, we can immediately conclude that the shear-thinning polymer exacerbates bypassing. We recommend the adoption of our redefined sweep indicators in any simulation suite. They provide instant understanding of sweep and hence can be complementary to standard practices of oil saturation mapping and of special value when analyzing the results of multiple realizations and/or development scenarios.
In this paper, we present a water-cut estimator utilizing the function approximation capability of an artificial neural network (ANN). The inputs to the ANN are optical sensor readings in a Red-Eye water-cut meter, which features the near-infrared (NIR) absorption spectroscopy technology. The initial training of the ANNwas done with a data set acquired from our multiphase flow-loop test facility, which was filled with live oil, water and gas. The test fluid stream was adjusted with good ranges of water-cut and gas-volume fractions which were supposed to cover the situations that can be foreseen in real production. However, clear discrepancies between the outputs of the ANN and the water-cut values from BS&W measurmentswere observedwhen the ANN was applied to actual production data measured by Red-Eye meters installed at two offshore wells. To address this issue and equip the ANN with self-adapting capability in real application, we propose a Bayesian approach to update the parameters of the ANN based on both initial flow-loop data and collected field data. The performance of the adapted ANN on both the data sets shows the effectiveness of the method.
Figure 1 shows the type of production response that is possible when applying a polymer gel treatment to a waterflood injection well to improve sweep efficiency. The figure shows the combined production-response of the four direct offsetting production wells to the gel-treated injection well. The gel treatment was applied for waterflood sweep-improvement purposes to the naturally fractured Embar carbonate formation surrounding Well O-7 of the highly mature SOB field in the Big Horn basin of Wyoming. The wide variations in water/oil ratio (WOR) and oil production rate are quite common in many of the well patterns of this highly fractured reservoir. Sydansk provides more details regarding the 20,000 bbl gel treatment.
This includes, during water- or gas-shutoff treatments, identifying the flow path of excessive water or gas production from its source to the production wellbore. The following procedure for gel technology selection is highly generalized, and the procedure should be modified as dictated by the actual reservoir conformance problem to be treated. If a service company or a company specializing in conformance treatment gels is to be involved, they should be consulted during each step of the selection process. A prerequisite is to eliminate all gel technologies, if any, that are prohibited by locally applicable safety or environmental regulations. First, determine the type of problem that is to be treated. That is, whether it is a matrix-rock problem or a high permeability anomaly problem, such as fractures. If treating a matrix-rock problem, decide if you need a gel for treating near-wellbore or deeply in the reservoir.
Proper placement of conformance improvement gels is key to achieving the desired results within the reservoir. The flow properties of a gelant or gel as it is being placed are important parameters. To date, for all known gelant solutions used in conformance improvement treatments (including polymer gelant solutions), these gelant solutions place themselves in all matrix-rock geological strata according to Darcy flow considerations and do so without any special selective placement in only the high-permeability strata and flow paths. Any placement of gel into, and the associated permeability reduction of, a low-permeability and/or high oil saturation strata in the near-wellbore region surrounding a radial-flow matrix-rock-reservoir well will almost always be counter productive to improving the conformance of that well. Thus, when applying a gel treatment, especially a near-wellbore gel treatment, to treat a vertical conformance problem of a radial-flow well in a matrix rock reservoir, mechanical zone isolation must be used to assure that the gelant is injected only into the high-permeability and/or low-oil-saturation geological strata to be treated.
This page focuses on important formula parameters and on temperature effects as they relate to gelation rate and gel strength of conformance treatment polymer gels. Figs. 1 through 4 relate to gel formula parameters and the effect of temperature for a specific CC/AP gel formula. Other oilfield polymer-gel technologies tend to follow similar relationships. The gel formula of Figs. 1 through 5 is a fracture-problem fluid-shutoff gel that has a rigid and soft Buna rubbery consistency. The gel was formulated in fresh water and contained 2.0 wt% active polyacrylamide (PAM) polymer possessing 11 million MW and 2% hydrolysis.