OGJ FOCUS: KHURAIS COMPLEX—1: Field development required best practices, leveraged technology

Resolution of new 3D seismic is much higher than the previous 2D seismic (Fig. 2).

Reservoir characterization

From the subsurface point of view, field development planning begins with geological and reservoir characterization. In the Khurais complex development, this included characterization of cores acquired from several vertical wells. These provided routine core descriptions and porosities and permeabilities of individual layers.

Because the information was sparse, the analysis used stochastic modeling to populate the matrix reservoir parameter arrays. The analysis also included fracture descriptions based on core studies as well as dynamic flow data, pressure transient tests, and drilling information, such as loss-circulation intervals.

Early in field development, work included drilling of horizontal wells for evaluation purposes and acquisition of image logs for fracture assessment and orientation.

The Khurais reservoir contains several types of fractures. The most numerous observed in cores are diffused fractures.¹ These are small scale tension fractures sometimes referred to as hairline fractures, microfractures, or background fractures. These fractures are most often bedbound within certain lithologies.

In the Khurais area, diffused fractures are widespread over the entire Arab-D with higher fracture density in the lower zones (Zones 2 and 3) in which matrix porosities and permeabilities are lower than in Zone 1.

Another fracture type appears as fracture swarms, sparse in occurrences and referred to as fracture corridors.^{2 3} Some of these are conduits for bringing water into the field. They also are referred to as fracture lineaments, derived from curvature analysis.

Khurais does not have large-scale fractures or faults that one can identify the throw on the seismic scale or on walk-away vertical seismic profiles (VSP) conducted in the area.

Dip analysis indicates that scattered fracture swarms are in an East-West to North 80° East trend (Fig. 4).

The Rose and Schmidt plots of fractures show a dominant North 80° East to East-West orientation (Fig. 4). These orientations are in agreement with limited fracture lineaments (fracture corridors or swarms) observed from seismic curvature analyses as strike-slip faults with minimal displacements (Fig. 5).^{2 3} One should note that while the appearance of fractures in Fig. 5 suggests a high fracture density, these lineaments are tens of kilometers apart.

Vertical-horizontal pilot wells delineated the structures (Fig. 6).

For cost-effectiveness, a series of vertical-horizontal pilot wells (Fig. 6) supplemented and refined the benchmarked 3D-seismic depth interpretations of the structure.

Subsequently, these wells were sidetracked and completed as water injectors. The horizontal laterals were placed just below the OWC for injection effectiveness with respect to pressure supporting the oil producing regions.

The 3D-seismic structure interpretations, combined with evaluation wells and pilot holes, helped in finding an additional small dome oil accumulation in the south of Abu Jifan, which subsequently was included as part of the Khurais complex development.

Similarly, the work delineated the south dome of Abu Jifan as a larger structure than previously mapped.

Advanced modeling

Concurrent with delineation and reservoir evaluation (data acquisition) efforts, optimization of the development plan needed to address several key issues in terms of risk mitigation. Although we faced a wide range of uncertainties in reservoir parameters, we based some major decisions on deterministic solutions derived from analytical, simulation, or mental (engineering judgment) models. These may prove costly because some had very little consideration to the probability and what if scenarios and resulted in actions taken without proper exit strategies.

In these cases, an engineer would build into the decision-making process a safety factor, or cushion, to make certain that failure is not an option. Under certain conditions, it is prudent to do so; however, this could carry a high business cost. The need for an uncertainty analysis for making decision, therefore, is a must.

For example, optimization of production offtake and associated requirements (such as number of injectors and producers, injection production ratio, depletion rates for different areas, sweep and recovery) is difficult because of the nonlinear nature of the optimization problem and the complex interactions between various operational parameters.

In this case, the analysis included a multiobjective function model. Another technical paper discussed the details of the methodology and its utility.⁴ This article excerpts some of the detail to clarify several points.

In field development, the most important questions and constraints are as follows:

• How much production offtake is optimal from each of the fields and reservoirs?

• What are the most optimal numbers of producers and injectors to be drilled? And what is the optimum well placement?

• How will producers and injectors affect the injection production ratio from each area?

• Does production from each area satisfy its depletion requirement?

• Do we produce or inject too much in areas that have a higher degree of fractures that may cause premature water breakthrough and thereby impair the sweep?

Optimizing these requirements is a difficult task because there are diverging requirements. This means that satisfying one requirement may be at the expense of the others. For example, a higher offtake rate from an area with better reservoir quality means drilling fewer producers for the same target rate, resulting in better developmental economics. This may violate the depletion criteria and may bring in premature water breakthrough, which can impair not only the reservoir sweep and conformance but also hydrocarbon recovery.

Another good example is producing at a depletion rate in an area with insufficient peripheral injection well locations, thereby potentially violating the pressure support requirements and consequently decreasing well productivity. This is where hard and soft constraints come into play and one has to assign weighted constraints.

The most important hard constraint, of course, is the total offtake rate for the increment development. The softest constraint is the number of wells required with the rest falling in between. With this in mind, the analysis divided the total offtake constraint into several areas, each with its specificities in terms of geometry and reservoir quality, in this case three fields and two reservoirs.

As previously mentioned, the hard or primary constraint is the total offtake and sustainability of the oil complex. The engineering analysis determined how much each area can produce by considering the following constraints:

• Keep depletion rate in balance among areas.

• Satisfy the injection production ratio, for example adequate injection has to support production and there must be enough injection wells to support the production.

• Minimize the withdrawal rate in areas with a higher degree of reservoir heterogenieties. A low production rate mitigates possible premature water breakthrough and allows reservoir performance to be observed, and evaluated to formulate optimum completion, and injection production strategy.

• Produce preferentially at a higher depletion rate in low structure areas to promote low structure sweep. This, in turn, lessens the production requirement in the higher structure area, allows better flood front sweep and conformance from low to high structure areas. This is particularly desirable in the case of gravity dominated bottoms-up sweep, as in the case for the reservoirs in the Khurais complex, judging from insights gathered from simulation models as well as from similar neighboring fields.

• Govern the production-injection strategy with prudent reservoir-management practices for oil offtake optimization from each reservoir and area to maximize the production plateau.

The multiobjective function program must optimize all of these constraints with regard to the soft constraint of economics, which is to reduce total development cost by minimizing the number of injectors and producers.

One can accomplished this by drilling wells on a priority basis in the most prolific area first without jeopardizing all other constraints. The key idea is establishment of hard and soft constraints that provide the venue for the optimization of all main requirements, including injection and producing well requirements, injection production ratio, production offtake, and depletion rate for individual areas.

The multiobjective function analysis represents the main focus of field development, such for Khurais.

Optimization of the development included determining a probability function for each reservoir parameter (Fig. 7).

Development work also included advanced modeling techniques and Monte Carlo simulations in conjunction with multiple realizations of 3D dual porosity-permeability models for development planning, including evaluation of the effect of various reservoir parameters on production using their individual probability functions (Figs. 7 and 8).

Waleed A. Al-Mulhim ([email protected]) is manager of the southern area reservoir management department in Saudi Aramco. Under his responsibilities, along with other fields, are greater Ghawar, Abqaiq, and all nonassociated gas reservoirs. Al-Mulhim oversaw the reservoir development of Khurais. He began his career with Saudi Aramco in 1984. Al-Mulhim has a MS in petroleum engineering from Stanford University.

Fahad A. Al-Ajmi is general supervisor for the Shayba-Manifa-Berri reservoir management division of Saudi Aramco. He previously was the general supervisor for the Khurais reservoir management division. Al-Ajmi has a BS in petroleum engineering from King Fahd University of Petroleum and Minerals, an MS in petroleum engineering from the University of Southern California, and PhD in petroleum engineering from Texas A&M University.

Mahdi A. Al-Shehab is a reservoir management supervisor for the Khurais Unit in the southern area reservoir management department of Saudi Aramco. He has worked in various positions at Saudi Aramco. Al-Shehab has a BS in petroleum engineering from King Fahd University of Petroleum and Minerals.

Tony R. Pham is a senior petroleum engineering consultant with more than 30 years of experience in the petroleum industry. Pham has a BS in petroleum engineering from Texas A&M University.

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